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Issue #11794: Reorganised logging documentation.

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Doc/howto/index.rst
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......@@ -19,6 +19,8 @@ Currently, the HOWTOs are:
descriptor.rst
doanddont.rst
functional.rst
logging.rst
logging-cookbook.rst
regex.rst
sockets.rst
sorting.rst
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Doc/howto/logging-cookbook.rst 0 → 100644
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.. _logging-cookbook:
================
Logging Cookbook
================
:Author: Vinay Sajip <vinay_sajip at red-dove dot com>
This page contains a number of recipes related to logging, which have been found
useful in the past.
.. currentmodule:: logging
Using logging in multiple modules
---------------------------------
Multiple calls to ``logging.getLogger('someLogger')`` return a reference to the
same logger object. This is true not only within the same module, but also
across modules as long as it is in the same Python interpreter process. It is
true for references to the same object; additionally, application code can
define and configure a parent logger in one module and create (but not
configure) a child logger in a separate module, and all logger calls to the
child will pass up to the parent. Here is a main module::
import logging
import auxiliary_module
# create logger with 'spam_application'
logger = logging.getLogger('spam_application')
logger.setLevel(logging.DEBUG)
# create file handler which logs even debug messages
fh = logging.FileHandler('spam.log')
fh.setLevel(logging.DEBUG)
# create console handler with a higher log level
ch = logging.StreamHandler()
ch.setLevel(logging.ERROR)
# create formatter and add it to the handlers
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
fh.setFormatter(formatter)
ch.setFormatter(formatter)
# add the handlers to the logger
logger.addHandler(fh)
logger.addHandler(ch)
logger.info('creating an instance of auxiliary_module.Auxiliary')
a = auxiliary_module.Auxiliary()
logger.info('created an instance of auxiliary_module.Auxiliary')
logger.info('calling auxiliary_module.Auxiliary.do_something')
a.do_something()
logger.info('finished auxiliary_module.Auxiliary.do_something')
logger.info('calling auxiliary_module.some_function()')
auxiliary_module.some_function()
logger.info('done with auxiliary_module.some_function()')
Here is the auxiliary module::
import logging
# create logger
module_logger = logging.getLogger('spam_application.auxiliary')
class Auxiliary:
def __init__(self):
self.logger = logging.getLogger('spam_application.auxiliary.Auxiliary')
self.logger.info('creating an instance of Auxiliary')
def do_something(self):
self.logger.info('doing something')
a = 1 + 1
self.logger.info('done doing something')
def some_function():
module_logger.info('received a call to "some_function"')
The output looks like this::
2005-03-23 23:47:11,663 - spam_application - INFO -
creating an instance of auxiliary_module.Auxiliary
2005-03-23 23:47:11,665 - spam_application.auxiliary.Auxiliary - INFO -
creating an instance of Auxiliary
2005-03-23 23:47:11,665 - spam_application - INFO -
created an instance of auxiliary_module.Auxiliary
2005-03-23 23:47:11,668 - spam_application - INFO -
calling auxiliary_module.Auxiliary.do_something
2005-03-23 23:47:11,668 - spam_application.auxiliary.Auxiliary - INFO -
doing something
2005-03-23 23:47:11,669 - spam_application.auxiliary.Auxiliary - INFO -
done doing something
2005-03-23 23:47:11,670 - spam_application - INFO -
finished auxiliary_module.Auxiliary.do_something
2005-03-23 23:47:11,671 - spam_application - INFO -
calling auxiliary_module.some_function()
2005-03-23 23:47:11,672 - spam_application.auxiliary - INFO -
received a call to 'some_function'
2005-03-23 23:47:11,673 - spam_application - INFO -
done with auxiliary_module.some_function()
Multiple handlers and formatters
--------------------------------
Loggers are plain Python objects. The :func:`addHandler` method has no minimum
or maximum quota for the number of handlers you may add. Sometimes it will be
beneficial for an application to log all messages of all severities to a text
file while simultaneously logging errors or above to the console. To set this
up, simply configure the appropriate handlers. The logging calls in the
application code will remain unchanged. Here is a slight modification to the
previous simple module-based configuration example::
import logging
logger = logging.getLogger('simple_example')
logger.setLevel(logging.DEBUG)
# create file handler which logs even debug messages
fh = logging.FileHandler('spam.log')
fh.setLevel(logging.DEBUG)
# create console handler with a higher log level
ch = logging.StreamHandler()
ch.setLevel(logging.ERROR)
# create formatter and add it to the handlers
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
ch.setFormatter(formatter)
fh.setFormatter(formatter)
# add the handlers to logger
logger.addHandler(ch)
logger.addHandler(fh)
# 'application' code
logger.debug('debug message')
logger.info('info message')
logger.warn('warn message')
logger.error('error message')
logger.critical('critical message')
Notice that the 'application' code does not care about multiple handlers. All
that changed was the addition and configuration of a new handler named *fh*.
The ability to create new handlers with higher- or lower-severity filters can be
very helpful when writing and testing an application. Instead of using many
``print`` statements for debugging, use ``logger.debug``: Unlike the print
statements, which you will have to delete or comment out later, the logger.debug
statements can remain intact in the source code and remain dormant until you
need them again. At that time, the only change that needs to happen is to
modify the severity level of the logger and/or handler to debug.
.. _multiple-destinations:
Logging to multiple destinations
--------------------------------
Let's say you want to log to console and file with different message formats and
in differing circumstances. Say you want to log messages with levels of DEBUG
and higher to file, and those messages at level INFO and higher to the console.
Let's also assume that the file should contain timestamps, but the console
messages should not. Here's how you can achieve this::
import logging
# set up logging to file - see previous section for more details
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s %(name)-12s %(levelname)-8s %(message)s',
datefmt='%m-%d %H:%M',
filename='/temp/myapp.log',
filemode='w')
# define a Handler which writes INFO messages or higher to the sys.stderr
console = logging.StreamHandler()
console.setLevel(logging.INFO)
# set a format which is simpler for console use
formatter = logging.Formatter('%(name)-12s: %(levelname)-8s %(message)s')
# tell the handler to use this format
console.setFormatter(formatter)
# add the handler to the root logger
logging.getLogger('').addHandler(console)
# Now, we can log to the root logger, or any other logger. First the root...
logging.info('Jackdaws love my big sphinx of quartz.')
# Now, define a couple of other loggers which might represent areas in your
# application:
logger1 = logging.getLogger('myapp.area1')
logger2 = logging.getLogger('myapp.area2')
logger1.debug('Quick zephyrs blow, vexing daft Jim.')
logger1.info('How quickly daft jumping zebras vex.')
logger2.warning('Jail zesty vixen who grabbed pay from quack.')
logger2.error('The five boxing wizards jump quickly.')
When you run this, on the console you will see ::
root : INFO Jackdaws love my big sphinx of quartz.
myapp.area1 : INFO How quickly daft jumping zebras vex.
myapp.area2 : WARNING Jail zesty vixen who grabbed pay from quack.
myapp.area2 : ERROR The five boxing wizards jump quickly.
and in the file you will see something like ::
10-22 22:19 root INFO Jackdaws love my big sphinx of quartz.
10-22 22:19 myapp.area1 DEBUG Quick zephyrs blow, vexing daft Jim.
10-22 22:19 myapp.area1 INFO How quickly daft jumping zebras vex.
10-22 22:19 myapp.area2 WARNING Jail zesty vixen who grabbed pay from quack.
10-22 22:19 myapp.area2 ERROR The five boxing wizards jump quickly.
As you can see, the DEBUG message only shows up in the file. The other messages
are sent to both destinations.
This example uses console and file handlers, but you can use any number and
combination of handlers you choose.
Configuration server example
----------------------------
Here is an example of a module using the logging configuration server::
import logging
import logging.config
import time
import os
# read initial config file
logging.config.fileConfig('logging.conf')
# create and start listener on port 9999
t = logging.config.listen(9999)
t.start()
logger = logging.getLogger('simpleExample')
try:
# loop through logging calls to see the difference
# new configurations make, until Ctrl+C is pressed
while True:
logger.debug('debug message')
logger.info('info message')
logger.warn('warn message')
logger.error('error message')
logger.critical('critical message')
time.sleep(5)
except KeyboardInterrupt:
# cleanup
logging.config.stopListening()
t.join()
And here is a script that takes a filename and sends that file to the server,
properly preceded with the binary-encoded length, as the new logging
configuration::
#!/usr/bin/env python
import socket, sys, struct
with open(sys.argv[1], 'rb') as f:
data_to_send = f.read()
HOST = 'localhost'
PORT = 9999
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
print('connecting...')
s.connect((HOST, PORT))
print('sending config...')
s.send(struct.pack('>L', len(data_to_send)))
s.send(data_to_send)
s.close()
print('complete')
.. _network-logging:
Sending and receiving logging events across a network
-----------------------------------------------------
Let's say you want to send logging events across a network, and handle them at
the receiving end. A simple way of doing this is attaching a
:class:`SocketHandler` instance to the root logger at the sending end::
import logging, logging.handlers
rootLogger = logging.getLogger('')
rootLogger.setLevel(logging.DEBUG)
socketHandler = logging.handlers.SocketHandler('localhost',
logging.handlers.DEFAULT_TCP_LOGGING_PORT)
# don't bother with a formatter, since a socket handler sends the event as
# an unformatted pickle
rootLogger.addHandler(socketHandler)
# Now, we can log to the root logger, or any other logger. First the root...
logging.info('Jackdaws love my big sphinx of quartz.')
# Now, define a couple of other loggers which might represent areas in your
# application:
logger1 = logging.getLogger('myapp.area1')
logger2 = logging.getLogger('myapp.area2')
logger1.debug('Quick zephyrs blow, vexing daft Jim.')
logger1.info('How quickly daft jumping zebras vex.')
logger2.warning('Jail zesty vixen who grabbed pay from quack.')
logger2.error('The five boxing wizards jump quickly.')
At the receiving end, you can set up a receiver using the :mod:`socketserver`
module. Here is a basic working example::
import pickle
import logging
import logging.handlers
import socketserver
import struct
class LogRecordStreamHandler(socketserver.StreamRequestHandler):
"""Handler for a streaming logging request.
This basically logs the record using whatever logging policy is
configured locally.
"""
def handle(self):
"""
Handle multiple requests - each expected to be a 4-byte length,
followed by the LogRecord in pickle format. Logs the record
according to whatever policy is configured locally.
"""
while True:
chunk = self.connection.recv(4)
if len(chunk) < 4:
break
slen = struct.unpack('>L', chunk)[0]
chunk = self.connection.recv(slen)
while len(chunk) < slen:
chunk = chunk + self.connection.recv(slen - len(chunk))
obj = self.unPickle(chunk)
record = logging.makeLogRecord(obj)
self.handleLogRecord(record)
def unPickle(self, data):
return pickle.loads(data)
def handleLogRecord(self, record):
# if a name is specified, we use the named logger rather than the one
# implied by the record.
if self.server.logname is not None:
name = self.server.logname
else:
name = record.name
logger = logging.getLogger(name)
# N.B. EVERY record gets logged. This is because Logger.handle
# is normally called AFTER logger-level filtering. If you want
# to do filtering, do it at the client end to save wasting
# cycles and network bandwidth!
logger.handle(record)
class LogRecordSocketReceiver(socketserver.ThreadingTCPServer):
"""
Simple TCP socket-based logging receiver suitable for testing.
"""
allow_reuse_address = 1
def __init__(self, host='localhost',
port=logging.handlers.DEFAULT_TCP_LOGGING_PORT,
handler=LogRecordStreamHandler):
socketserver.ThreadingTCPServer.__init__(self, (host, port), handler)
self.abort = 0
self.timeout = 1
self.logname = None
def serve_until_stopped(self):
import select
abort = 0
while not abort:
rd, wr, ex = select.select([self.socket.fileno()],
[], [],
self.timeout)
if rd:
self.handle_request()
abort = self.abort
def main():
logging.basicConfig(
format='%(relativeCreated)5d %(name)-15s %(levelname)-8s %(message)s')
tcpserver = LogRecordSocketReceiver()
print('About to start TCP server...')
tcpserver.serve_until_stopped()
if __name__ == '__main__':
main()
First run the server, and then the client. On the client side, nothing is
printed on the console; on the server side, you should see something like::
About to start TCP server...
59 root INFO Jackdaws love my big sphinx of quartz.
59 myapp.area1 DEBUG Quick zephyrs blow, vexing daft Jim.
69 myapp.area1 INFO How quickly daft jumping zebras vex.
69 myapp.area2 WARNING Jail zesty vixen who grabbed pay from quack.
69 myapp.area2 ERROR The five boxing wizards jump quickly.
Note that there are some security issues with pickle in some scenarios. If
these affect you, you can use an alternative serialization scheme by overriding
the :meth:`makePickle` method and implementing your alternative there, as
well as adapting the above script to use your alternative serialization.
.. _context-info:
Adding contextual information to your logging output
----------------------------------------------------
Sometimes you want logging output to contain contextual information in
addition to the parameters passed to the logging call. For example, in a
networked application, it may be desirable to log client-specific information
in the log (e.g. remote client's username, or IP address). Although you could
use the *extra* parameter to achieve this, it's not always convenient to pass
the information in this way. While it might be tempting to create
:class:`Logger` instances on a per-connection basis, this is not a good idea
because these instances are not garbage collected. While this is not a problem
in practice, when the number of :class:`Logger` instances is dependent on the
level of granularity you want to use in logging an application, it could
be hard to manage if the number of :class:`Logger` instances becomes
effectively unbounded.
Using LoggerAdapters to impart contextual information
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
An easy way in which you can pass contextual information to be output along
with logging event information is to use the :class:`LoggerAdapter` class.
This class is designed to look like a :class:`Logger`, so that you can call
:meth:`debug`, :meth:`info`, :meth:`warning`, :meth:`error`,
:meth:`exception`, :meth:`critical` and :meth:`log`. These methods have the
same signatures as their counterparts in :class:`Logger`, so you can use the
two types of instances interchangeably.
When you create an instance of :class:`LoggerAdapter`, you pass it a
:class:`Logger` instance and a dict-like object which contains your contextual
information. When you call one of the logging methods on an instance of
:class:`LoggerAdapter`, it delegates the call to the underlying instance of
:class:`Logger` passed to its constructor, and arranges to pass the contextual
information in the delegated call. Here's a snippet from the code of
:class:`LoggerAdapter`::
def debug(self, msg, *args, **kwargs):
"""
Delegate a debug call to the underlying logger, after adding
contextual information from this adapter instance.
"""
msg, kwargs = self.process(msg, kwargs)
self.logger.debug(msg, *args, **kwargs)
The :meth:`process` method of :class:`LoggerAdapter` is where the contextual
information is added to the logging output. It's passed the message and
keyword arguments of the logging call, and it passes back (potentially)
modified versions of these to use in the call to the underlying logger. The
default implementation of this method leaves the message alone, but inserts
an 'extra' key in the keyword argument whose value is the dict-like object
passed to the constructor. Of course, if you had passed an 'extra' keyword
argument in the call to the adapter, it will be silently overwritten.
The advantage of using 'extra' is that the values in the dict-like object are
merged into the :class:`LogRecord` instance's __dict__, allowing you to use
customized strings with your :class:`Formatter` instances which know about
the keys of the dict-like object. If you need a different method, e.g. if you
want to prepend or append the contextual information to the message string,
you just need to subclass :class:`LoggerAdapter` and override :meth:`process`
to do what you need. Here's an example script which uses this class, which
also illustrates what dict-like behaviour is needed from an arbitrary
'dict-like' object for use in the constructor::
import logging
class ConnInfo:
"""
An example class which shows how an arbitrary class can be used as
the 'extra' context information repository passed to a LoggerAdapter.
"""
def __getitem__(self, name):
"""
To allow this instance to look like a dict.
"""
from random import choice
if name == 'ip':
result = choice(['127.0.0.1', '192.168.0.1'])
elif name == 'user':
result = choice(['jim', 'fred', 'sheila'])
else:
result = self.__dict__.get(name, '?')
return result
def __iter__(self):
"""
To allow iteration over keys, which will be merged into
the LogRecord dict before formatting and output.
"""
keys = ['ip', 'user']
keys.extend(self.__dict__.keys())
return keys.__iter__()
if __name__ == '__main__':
from random import choice
levels = (logging.DEBUG, logging.INFO, logging.WARNING, logging.ERROR, logging.CRITICAL)
a1 = logging.LoggerAdapter(logging.getLogger('a.b.c'),
{ 'ip' : '123.231.231.123', 'user' : 'sheila' })
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)-15s %(name)-5s %(levelname)-8s IP: %(ip)-15s User: %(user)-8s %(message)s')
a1.debug('A debug message')
a1.info('An info message with %s', 'some parameters')
a2 = logging.LoggerAdapter(logging.getLogger('d.e.f'), ConnInfo())
for x in range(10):
lvl = choice(levels)
lvlname = logging.getLevelName(lvl)
a2.log(lvl, 'A message at %s level with %d %s', lvlname, 2, 'parameters')
When this script is run, the output should look something like this::
2008-01-18 14:49:54,023 a.b.c DEBUG IP: 123.231.231.123 User: sheila A debug message
2008-01-18 14:49:54,023 a.b.c INFO IP: 123.231.231.123 User: sheila An info message with some parameters
2008-01-18 14:49:54,023 d.e.f CRITICAL IP: 192.168.0.1 User: jim A message at CRITICAL level with 2 parameters
2008-01-18 14:49:54,033 d.e.f INFO IP: 192.168.0.1 User: jim A message at INFO level with 2 parameters
2008-01-18 14:49:54,033 d.e.f WARNING IP: 192.168.0.1 User: sheila A message at WARNING level with 2 parameters
2008-01-18 14:49:54,033 d.e.f ERROR IP: 127.0.0.1 User: fred A message at ERROR level with 2 parameters
2008-01-18 14:49:54,033 d.e.f ERROR IP: 127.0.0.1 User: sheila A message at ERROR level with 2 parameters
2008-01-18 14:49:54,033 d.e.f WARNING IP: 192.168.0.1 User: sheila A message at WARNING level with 2 parameters
2008-01-18 14:49:54,033 d.e.f WARNING IP: 192.168.0.1 User: jim A message at WARNING level with 2 parameters
2008-01-18 14:49:54,033 d.e.f INFO IP: 192.168.0.1 User: fred A message at INFO level with 2 parameters
2008-01-18 14:49:54,033 d.e.f WARNING IP: 192.168.0.1 User: sheila A message at WARNING level with 2 parameters
2008-01-18 14:49:54,033 d.e.f WARNING IP: 127.0.0.1 User: jim A message at WARNING level with 2 parameters
.. _filters-contextual:
Using Filters to impart contextual information
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
You can also add contextual information to log output using a user-defined
:class:`Filter`. ``Filter`` instances are allowed to modify the ``LogRecords``
passed to them, including adding additional attributes which can then be output
using a suitable format string, or if needed a custom :class:`Formatter`.
For example in a web application, the request being processed (or at least,
the interesting parts of it) can be stored in a threadlocal
(:class:`threading.local`) variable, and then accessed from a ``Filter`` to
add, say, information from the request - say, the remote IP address and remote
user's username - to the ``LogRecord``, using the attribute names 'ip' and
'user' as in the ``LoggerAdapter`` example above. In that case, the same format
string can be used to get similar output to that shown above. Here's an example
script::
import logging
from random import choice
class ContextFilter(logging.Filter):
"""
This is a filter which injects contextual information into the log.
Rather than use actual contextual information, we just use random
data in this demo.
"""
USERS = ['jim', 'fred', 'sheila']
IPS = ['123.231.231.123', '127.0.0.1', '192.168.0.1']
def filter(self, record):
record.ip = choice(ContextFilter.IPS)
record.user = choice(ContextFilter.USERS)
return True
if __name__ == '__main__':
levels = (logging.DEBUG, logging.INFO, logging.WARNING, logging.ERROR, logging.CRITICAL)
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)-15s %(name)-5s %(levelname)-8s IP: %(ip)-15s User: %(user)-8s %(message)s')
a1 = logging.getLogger('a.b.c')
a2 = logging.getLogger('d.e.f')
f = ContextFilter()
a1.addFilter(f)
a2.addFilter(f)
a1.debug('A debug message')
a1.info('An info message with %s', 'some parameters')
for x in range(10):
lvl = choice(levels)
lvlname = logging.getLevelName(lvl)
a2.log(lvl, 'A message at %s level with %d %s', lvlname, 2, 'parameters')
which, when run, produces something like::
2010-09-06 22:38:15,292 a.b.c DEBUG IP: 123.231.231.123 User: fred A debug message
2010-09-06 22:38:15,300 a.b.c INFO IP: 192.168.0.1 User: sheila An info message with some parameters
2010-09-06 22:38:15,300 d.e.f CRITICAL IP: 127.0.0.1 User: sheila A message at CRITICAL level with 2 parameters
2010-09-06 22:38:15,300 d.e.f ERROR IP: 127.0.0.1 User: jim A message at ERROR level with 2 parameters
2010-09-06 22:38:15,300 d.e.f DEBUG IP: 127.0.0.1 User: sheila A message at DEBUG level with 2 parameters
2010-09-06 22:38:15,300 d.e.f ERROR IP: 123.231.231.123 User: fred A message at ERROR level with 2 parameters
2010-09-06 22:38:15,300 d.e.f CRITICAL IP: 192.168.0.1 User: jim A message at CRITICAL level with 2 parameters
2010-09-06 22:38:15,300 d.e.f CRITICAL IP: 127.0.0.1 User: sheila A message at CRITICAL level with 2 parameters
2010-09-06 22:38:15,300 d.e.f DEBUG IP: 192.168.0.1 User: jim A message at DEBUG level with 2 parameters
2010-09-06 22:38:15,301 d.e.f ERROR IP: 127.0.0.1 User: sheila A message at ERROR level with 2 parameters
2010-09-06 22:38:15,301 d.e.f DEBUG IP: 123.231.231.123 User: fred A message at DEBUG level with 2 parameters
2010-09-06 22:38:15,301 d.e.f INFO IP: 123.231.231.123 User: fred A message at INFO level with 2 parameters
.. _multiple-processes:
Logging to a single file from multiple processes
------------------------------------------------
Although logging is thread-safe, and logging to a single file from multiple
threads in a single process *is* supported, logging to a single file from
*multiple processes* is *not* supported, because there is no standard way to
serialize access to a single file across multiple processes in Python. If you
need to log to a single file from multiple processes, one way of doing this is
to have all the processes log to a :class:`SocketHandler`, and have a separate
process which implements a socket server which reads from the socket and logs
to file. (If you prefer, you can dedicate one thread in one of the existing
processes to perform this function.) The following section documents this
approach in more detail and includes a working socket receiver which can be
used as a starting point for you to adapt in your own applications.
If you are using a recent version of Python which includes the
:mod:`multiprocessing` module, you could write your own handler which uses the
:class:`Lock` class from this module to serialize access to the file from
your processes. The existing :class:`FileHandler` and subclasses do not make
use of :mod:`multiprocessing` at present, though they may do so in the future.
Note that at present, the :mod:`multiprocessing` module does not provide
working lock functionality on all platforms (see
http://bugs.python.org/issue3770).
.. currentmodule:: logging.handlers
Using file rotation
-------------------
.. sectionauthor:: Doug Hellmann, Vinay Sajip (changes)
.. (see <http://blog.doughellmann.com/2007/05/pymotw-logging.html>)
Sometimes you want to let a log file grow to a certain size, then open a new
file and log to that. You may want to keep a certain number of these files, and
when that many files have been created, rotate the files so that the number of
files and the size of the files both remain bounded. For this usage pattern, the
logging package provides a :class:`RotatingFileHandler`::
import glob
import logging
import logging.handlers
LOG_FILENAME = 'logging_rotatingfile_example.out'
# Set up a specific logger with our desired output level
my_logger = logging.getLogger('MyLogger')
my_logger.setLevel(logging.DEBUG)
# Add the log message handler to the logger
handler = logging.handlers.RotatingFileHandler(
LOG_FILENAME, maxBytes=20, backupCount=5)
my_logger.addHandler(handler)
# Log some messages
for i in range(20):
my_logger.debug('i = %d' % i)
# See what files are created
logfiles = glob.glob('%s*' % LOG_FILENAME)
for filename in logfiles:
print(filename)
The result should be 6 separate files, each with part of the log history for the
application::
logging_rotatingfile_example.out
logging_rotatingfile_example.out.1
logging_rotatingfile_example.out.2
logging_rotatingfile_example.out.3
logging_rotatingfile_example.out.4
logging_rotatingfile_example.out.5
The most current file is always :file:`logging_rotatingfile_example.out`,
and each time it reaches the size limit it is renamed with the suffix
``.1``. Each of the existing backup files is renamed to increment the suffix
(``.1`` becomes ``.2``, etc.) and the ``.6`` file is erased.
Obviously this example sets the log length much much too small as an extreme
example. You would want to set *maxBytes* to an appropriate value.
Doc/howto/logging.rst 0 → 100644
View file @ 5dbca9cc
=============
Logging HOWTO
=============
:Author: Vinay Sajip <vinay_sajip at red-dove dot com>
.. _logging-basic-tutorial:
.. currentmodule:: logging
Basic Logging Tutorial
----------------------
Logging is a means of tracking events that happen when some software runs. The
software's developer adds logging calls to their code to indicate that certain
events have occurred. An event is described by a descriptive message which can
optionally contain variable data (i.e. data that is potentially different for
each occurrence of the event). Events also have an importance which the
developer ascribes to the event; the importance can also be called the *level*
or *severity*.
When to use logging
^^^^^^^^^^^^^^^^^^^
Logging provides a set of convenience functions for simple logging usage. These
are :func:`debug`, :func:`info`, :func:`warning`, :func:`error` and
:func:`critical`. To determine when to use logging, see the table below, which
states, for each of a set of common tasks, the best tool to use for it.
+-------------------------------------+--------------------------------------+
| Task you want to perform | The best tool for the task |
+=====================================+======================================+
| Display console output for ordinary | :func:`print` |
| usage of a command line script or | |
| program | |
+-------------------------------------+--------------------------------------+
| Report events that occur during | :func:`logging.info` (or |
| normal operation of a program (e.g. | :func:`logging.debug` for very |
| for status monitoring or fault | detailed output for diagnostic |
| investigation) | purposes) |
+-------------------------------------+--------------------------------------+
| Issue a warning regarding a | :func:`warnings.warn` in library |
| particular runtime event | code if the issue is avoidable and |
| | the client application should be |
| | modified to eliminate the warning |
| | |
| | :func:`logging.warning` if there is |
| | nothing the client application can do|
| | about the situation, but the event |
| | should still be noted |
+-------------------------------------+--------------------------------------+
| Report an error regarding a | Raise an exception |
| particular runtime event | |
+-------------------------------------+--------------------------------------+
| Report suppression of an error | :func:`logging.error`, |
| without raising an exception (e.g. | :func:`logging.exception` or |
| error handler in a long-running | :func:`logging.critical` as |
| server process) | appropriate for the specific error |
| | and application domain |
+-------------------------------------+--------------------------------------+
The logging functions are named after the level or severity of the events
they are used to track. The standard levels and their applicability are
described below (in increasing order of severity):
+--------------+---------------------------------------------+
| Level | When it's used |
+==============+=============================================+
| ``DEBUG`` | Detailed information, typically of interest |
| | only when diagnosing problems. |
+--------------+---------------------------------------------+
| ``INFO`` | Confirmation that things are working as |
| | expected. |
+--------------+---------------------------------------------+
| ``WARNING`` | An indication that something unexpected |
| | happened, or indicative of some problem in |
| | the near future (e.g. 'disk space low'). |
| | The software is still working as expected. |
+--------------+---------------------------------------------+
| ``ERROR`` | Due to a more serious problem, the software |
| | has not been able to perform some function. |
+--------------+---------------------------------------------+
| ``CRITICAL`` | A serious error, indicating that the program|
| | itself may be unable to continue running. |
+--------------+---------------------------------------------+
The default level is ``WARNING``, which means that only events of this level
and above will be tracked, unless the logging package is configured to do
otherwise.
Events that are tracked can be handled in different ways. The simplest way of
handling tracked events is to print them to the console. Another common way
is to write them to a disk file.
.. _howto-minimal-example:
A simple example
^^^^^^^^^^^^^^^^
A very simple example is::
import logging
logging.warning('Watch out!') # will print a message to the console
logging.info('I told you so') # will not print anything
If you type these lines into a script and run it, you'll see::
WARNING:root:Watch out!
printed out on the console. The ``INFO`` message doesn't appear because the
default level is ``WARNING``. The printed message includes the indication of
the level and the description of the event provided in the logging call, i.e.
'Watch out!'. Don't worry about the 'root' part for now: it will be explained
later. The actual output can be formatted quite flexibly if you need that;
formatting options will also be explained later.
Logging to a file
^^^^^^^^^^^^^^^^^
A very common situation is that of recording logging events in a file, so let's
look at that next::
import logging
logging.basicConfig(filename='example.log',level=logging.DEBUG)
logging.debug('This message should go to the log file')
logging.info('So should this')
logging.warning('And this, too')
And now if we open the file and look at what we have, we should find the log
messages::
DEBUG:root:This message should go to the log file
INFO:root:So should this
WARNING:root:And this, too
This example also shows how you can set the logging level which acts as the
threshold for tracking. In this case, because we set the threshold to
``DEBUG``, all of the messages were printed.
If you want to set the logging level from a command-line option such as::
--log=INFO
and you have the value of the parameter passed for ``--log`` in some variable
*loglevel*, you can use::
getattr(logging, loglevel.upper())
to get the value which you'll pass to :func:`basicConfig` via the *level*
argument. You may want to error check any user input value, perhaps as in the
following example::
# assuming loglevel is bound to the string value obtained from the
# command line argument. Convert to upper case to allow the user to
# specify --log=DEBUG or --log=debug
numeric_level = getattr(logging, loglevel.upper(), None)
if not isinstance(numeric_level, int):
raise ValueError('Invalid log level: %s' % loglevel)
logging.basicConfig(level=numeric_level, ...)
The call to :func:`basicConfig` should come *before* any calls to :func:`debug`,
:func:`info` etc. As it's intended as a one-off simple configuration facility,
only the first call will actually do anything: subsequent calls are effectively
no-ops.
If you run the above script several times, the messages from successive runs
are appended to the file *example.log*. If you want each run to start afresh,
not remembering the messages from earlier runs, you can specify the *filemode*
argument, by changing the call in the above example to::
logging.basicConfig(filename='example.log', filemode='w', level=logging.DEBUG)
The output will be the same as before, but the log file is no longer appended
to, so the messages from earlier runs are lost.
Logging from multiple modules
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
If your program consists of multiple modules, here's an example of how you
could organize logging in it::
# myapp.py
import logging
import mylib
def main():
logging.basicConfig(filename='myapp.log', level=logging.INFO)
logging.info('Started')
mylib.do_something()
logging.info('Finished')
if __name__ == '__main__':
main()
::
# mylib.py
import logging
def do_something():
logging.info('Doing something')
If you run *myapp.py*, you should see this in *myapp.log*::
INFO:root:Started
INFO:root:Doing something
INFO:root:Finished
which is hopefully what you were expecting to see. You can generalize this to
multiple modules, using the pattern in *mylib.py*. Note that for this simple
usage pattern, you won't know, by looking in the log file, *where* in your
application your messages came from, apart from looking at the event
description. If you want to track the location of your messages, you'll need
to refer to the documentation beyond the tutorial level -- see
:ref:`logging-advanced-tutorial`.
Logging variable data
^^^^^^^^^^^^^^^^^^^^^
To log variable data, use a format string for the event description message and
append the variable data as arguments. For example::
import logging
logging.warning('%s before you %s', 'Look', 'leap!')
will display::
WARNING:root:Look before you leap!
As you can see, merging of variable data into the event description message
uses the old, %-style of string formatting. This is for backwards
compatibility: the logging package pre-dates newer formatting options such as
:meth:`str.format` and :class:`string.Template`. These newer formatting
options *are* supported, but exploring them is outside the scope of this
tutorial.
Changing the format of displayed messages
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
To change the format which is used to display messages, you need to
specify the format you want to use::
import logging
logging.basicConfig(format='%(levelname)s:%(message)s', level=logging.DEBUG)
logging.debug('This message should appear on the console')
logging.info('So should this')
logging.warning('And this, too')
which would print::
DEBUG:This message should appear on the console
INFO:So should this
WARNING:And this, too
Notice that the 'root' which appeared in earlier examples has disappeared. For
a full set of things that can appear in format strings, you can refer to the
documentation for :ref:`logrecord-attributes`, but for simple usage, you just
need the *levelname* (severity), *message* (event description, including
variable data) and perhaps to display when the event occurred. This is
described in the next section.
Displaying the date/time in messages
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
To display the date and time of an event, you would place '%(asctime)s' in
your format string::
import logging
logging.basicConfig(format='%(asctime)s %(message)s')
logging.warning('is when this event was logged.')
which should print something like this::
2010-12-12 11:41:42,612 is when this event was logged.
The default format for date/time display (shown above) is ISO8601. If you need
more control over the formatting of the date/time, provide a *datefmt*
argument to ``basicConfig``, as in this example::
import logging
logging.basicConfig(format='%(asctime)s %(message)s', datefmt='%m/%d/%Y %I:%M:%S %p')
logging.warning('is when this event was logged.')
which would display something like this::
12/12/2010 11:46:36 AM is when this event was logged.
The format of the *datefmt* argument is the same as supported by
:func:`time.strftime`.
Next Steps
^^^^^^^^^^
That concludes the basic tutorial. It should be enough to get you up and
running with logging. There's a lot more that the logging package offers, but
to get the best out of it, you'll need to invest a little more of your time in
reading the following sections. If you're ready for that, grab some of your
favourite beverage and carry on.
If your logging needs are simple, then use the above examples to incorporate
logging into your own scripts, and if you run into problems or don't
understand something, please post a question on the comp.lang.python Usenet
group (available at http://groups.google.com/group/comp.lang.python) and you
should receive help before too long.
Still here? You can carry on reading the next few sections, which provide a
slightly more advanced/in-depth tutorial than the basic one above. After that,
you can take a look at the :ref:`logging-cookbook`.
.. _logging-advanced-tutorial:
Advanced Logging Tutorial
-------------------------
The logging library takes a modular approach and offers several categories
of components: loggers, handlers, filters, and formatters.
* Loggers expose the interface that application code directly uses.
* Handlers send the log records (created by loggers) to the appropriate
destination.
* Filters provide a finer grained facility for determining which log records
to output.
* Formatters specify the layout of log records in the final output.
Logging is performed by calling methods on instances of the :class:`Logger`
class (hereafter called :dfn:`loggers`). Each instance has a name, and they are
conceptually arranged in a namespace hierarchy using dots (periods) as
separators. For example, a logger named 'scan' is the parent of loggers
'scan.text', 'scan.html' and 'scan.pdf'. Logger names can be anything you want,
and indicate the area of an application in which a logged message originates.
A good convention to use when naming loggers is to use a module-level logger,
in each module which uses logging, named as follows::
logger = logging.getLogger(__name__)
This means that logger names track the package/module hierarchy, and it's
intuitively obvious where events are logged just from the logger name.
The root of the hierarchy of loggers is called the root logger. That's the
logger used by the functions :func:`debug`, :func:`info`, :func:`warning`,
:func:`error` and :func:`critical`, which just call the same-named method of
the root logger. The functions and the methods have the same signatures. The
root logger's name is printed as 'root' in the logged output.
It is, of course, possible to log messages to different destinations. Support
is included in the package for writing log messages to files, HTTP GET/POST
locations, email via SMTP, generic sockets, or OS-specific logging mechanisms
such as syslog or the Windows NT event log. Destinations are served by
:dfn:`handler` classes. You can create your own log destination class if you
have special requirements not met by any of the built-in handler classes.
By default, no destination is set for any logging messages. You can specify
a destination (such as console or file) by using :func:`basicConfig` as in the
tutorial examples. If you call the functions :func:`debug`, :func:`info`,
:func:`warning`, :func:`error` and :func:`critical`, they will check to see
if no destination is set; and if one is not set, they will set a destination
of the console (``sys.stderr``) and a default format for the displayed
message before delegating to the root logger to do the actual message output.
The default format set by :func:`basicConfig` for messages is::
severity:logger name:message
You can change this by passing a format string to :func:`basicConfig` with the
*format* keyword argument. For all options regarding how a format string is
constructed, see :ref:`formatter-objects`.
Loggers
^^^^^^^
:class:`Logger` objects have a threefold job. First, they expose several
methods to application code so that applications can log messages at runtime.
Second, logger objects determine which log messages to act upon based upon
severity (the default filtering facility) or filter objects. Third, logger
objects pass along relevant log messages to all interested log handlers.
The most widely used methods on logger objects fall into two categories:
configuration and message sending.
These are the most common configuration methods:
* :meth:`Logger.setLevel` specifies the lowest-severity log message a logger
will handle, where debug is the lowest built-in severity level and critical
is the highest built-in severity. For example, if the severity level is
INFO, the logger will handle only INFO, WARNING, ERROR, and CRITICAL messages
and will ignore DEBUG messages.
* :meth:`Logger.addHandler` and :meth:`Logger.removeHandler` add and remove
handler objects from the logger object. Handlers are covered in more detail
in :ref:`handler-basic`.
* :meth:`Logger.addFilter` and :meth:`Logger.removeFilter` add and remove filter
objects from the logger object. Filters are covered in more detail in
:ref:`filter`.
You don't need to always call these methods on every logger you create. See the
last two paragraphs in this section.
With the logger object configured, the following methods create log messages:
* :meth:`Logger.debug`, :meth:`Logger.info`, :meth:`Logger.warning`,
:meth:`Logger.error`, and :meth:`Logger.critical` all create log records with
a message and a level that corresponds to their respective method names. The
message is actually a format string, which may contain the standard string
substitution syntax of :const:`%s`, :const:`%d`, :const:`%f`, and so on. The
rest of their arguments is a list of objects that correspond with the
substitution fields in the message. With regard to :const:`**kwargs`, the
logging methods care only about a keyword of :const:`exc_info` and use it to
determine whether to log exception information.
* :meth:`Logger.exception` creates a log message similar to
:meth:`Logger.error`. The difference is that :meth:`Logger.exception` dumps a
stack trace along with it. Call this method only from an exception handler.
* :meth:`Logger.log` takes a log level as an explicit argument. This is a
little more verbose for logging messages than using the log level convenience
methods listed above, but this is how to log at custom log levels.
:func:`getLogger` returns a reference to a logger instance with the specified
name if it is provided, or ``root`` if not. The names are period-separated
hierarchical structures. Multiple calls to :func:`getLogger` with the same name
will return a reference to the same logger object. Loggers that are further
down in the hierarchical list are children of loggers higher up in the list.
For example, given a logger with a name of ``foo``, loggers with names of
``foo.bar``, ``foo.bar.baz``, and ``foo.bam`` are all descendants of ``foo``.
Loggers have a concept of *effective level*. If a level is not explicitly set
on a logger, the level of its parent is used instead as its effective level.
If the parent has no explicit level set, *its* parent is examined, and so on -
all ancestors are searched until an explicitly set level is found. The root
logger always has an explicit level set (``WARNING`` by default). When deciding
whether to process an event, the effective level of the logger is used to
determine whether the event is passed to the logger's handlers.
Child loggers propagate messages up to the handlers associated with their
ancestor loggers. Because of this, it is unnecessary to define and configure
handlers for all the loggers an application uses. It is sufficient to
configure handlers for a top-level logger and create child loggers as needed.
(You can, however, turn off propagation by setting the *propagate*
attribute of a logger to *False*.)
.. _handler-basic:
Handlers
^^^^^^^^
:class:`~logging.Handler` objects are responsible for dispatching the
appropriate log messages (based on the log messages' severity) to the handler's
specified destination. Logger objects can add zero or more handler objects to
themselves with an :func:`addHandler` method. As an example scenario, an
application may want to send all log messages to a log file, all log messages
of error or higher to stdout, and all messages of critical to an email address.
This scenario requires three individual handlers where each handler is
responsible for sending messages of a specific severity to a specific location.
The standard library includes quite a few handler types (see
:ref:`useful-handlers`); the tutorials use mainly :class:`StreamHandler` and
:class:`FileHandler` in its examples.
There are very few methods in a handler for application developers to concern
themselves with. The only handler methods that seem relevant for application
developers who are using the built-in handler objects (that is, not creating
custom handlers) are the following configuration methods:
* The :meth:`Handler.setLevel` method, just as in logger objects, specifies the
lowest severity that will be dispatched to the appropriate destination. Why
are there two :func:`setLevel` methods? The level set in the logger
determines which severity of messages it will pass to its handlers. The level
set in each handler determines which messages that handler will send on.
* :func:`setFormatter` selects a Formatter object for this handler to use.
* :func:`addFilter` and :func:`removeFilter` respectively configure and
deconfigure filter objects on handlers.
Application code should not directly instantiate and use instances of
:class:`Handler`. Instead, the :class:`Handler` class is a base class that
defines the interface that all handlers should have and establishes some
default behavior that child classes can use (or override).
Formatters
^^^^^^^^^^
Formatter objects configure the final order, structure, and contents of the log
message. Unlike the base :class:`logging.Handler` class, application code may
instantiate formatter classes, although you could likely subclass the formatter
if your application needs special behavior. The constructor takes two
optional arguments -- a message format string and a date format string.
.. method:: logging.Formatter.__init__(fmt=None, datefmt=None)
If there is no message format string, the default is to use the
raw message. If there is no date format string, the default date format is::
%Y-%m-%d %H:%M:%S
with the milliseconds tacked on at the end.
The message format string uses ``%(<dictionary key>)s`` styled string
substitution; the possible keys are documented in :ref:`logrecord-attributes`.
The following message format string will log the time in a human-readable
format, the severity of the message, and the contents of the message, in that
order::
'%(asctime)s - %(levelname)s - %(message)s'
Formatters use a user-configurable function to convert the creation time of a
record to a tuple. By default, :func:`time.localtime` is used; to change this
for a particular formatter instance, set the ``converter`` attribute of the
instance to a function with the same signature as :func:`time.localtime` or
:func:`time.gmtime`. To change it for all formatters, for example if you want
all logging times to be shown in GMT, set the ``converter`` attribute in the
Formatter class (to ``time.gmtime`` for GMT display).
Configuring Logging
^^^^^^^^^^^^^^^^^^^
.. currentmodule:: logging.config
Programmers can configure logging in three ways:
1. Creating loggers, handlers, and formatters explicitly using Python
code that calls the configuration methods listed above.
2. Creating a logging config file and reading it using the :func:`fileConfig`
function.
3. Creating a dictionary of configuration information and passing it
to the :func:`dictConfig` function.
For the reference documentation on the last two options, see
:ref:`logging-config-api`. The following example configures a very simple
logger, a console handler, and a simple formatter using Python code::
import logging
# create logger
logger = logging.getLogger('simple_example')
logger.setLevel(logging.DEBUG)
# create console handler and set level to debug
ch = logging.StreamHandler()
ch.setLevel(logging.DEBUG)
# create formatter
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
# add formatter to ch
ch.setFormatter(formatter)
# add ch to logger
logger.addHandler(ch)
# 'application' code
logger.debug('debug message')
logger.info('info message')
logger.warn('warn message')
logger.error('error message')
logger.critical('critical message')
Running this module from the command line produces the following output::
$ python simple_logging_module.py
2005-03-19 15:10:26,618 - simple_example - DEBUG - debug message
2005-03-19 15:10:26,620 - simple_example - INFO - info message
2005-03-19 15:10:26,695 - simple_example - WARNING - warn message
2005-03-19 15:10:26,697 - simple_example - ERROR - error message
2005-03-19 15:10:26,773 - simple_example - CRITICAL - critical message
The following Python module creates a logger, handler, and formatter nearly
identical to those in the example listed above, with the only difference being
the names of the objects::
import logging
import logging.config
logging.config.fileConfig('logging.conf')
# create logger
logger = logging.getLogger('simpleExample')
# 'application' code
logger.debug('debug message')
logger.info('info message')
logger.warn('warn message')
logger.error('error message')
logger.critical('critical message')
Here is the logging.conf file::
[loggers]
keys=root,simpleExample
[handlers]
keys=consoleHandler
[formatters]
keys=simpleFormatter
[logger_root]
level=DEBUG
handlers=consoleHandler
[logger_simpleExample]
level=DEBUG
handlers=consoleHandler
qualname=simpleExample
propagate=0
[handler_consoleHandler]
class=StreamHandler
level=DEBUG
formatter=simpleFormatter
args=(sys.stdout,)
[formatter_simpleFormatter]
format=%(asctime)s - %(name)s - %(levelname)s - %(message)s
datefmt=
The output is nearly identical to that of the non-config-file-based example::
$ python simple_logging_config.py
2005-03-19 15:38:55,977 - simpleExample - DEBUG - debug message
2005-03-19 15:38:55,979 - simpleExample - INFO - info message
2005-03-19 15:38:56,054 - simpleExample - WARNING - warn message
2005-03-19 15:38:56,055 - simpleExample - ERROR - error message
2005-03-19 15:38:56,130 - simpleExample - CRITICAL - critical message
You can see that the config file approach has a few advantages over the Python
code approach, mainly separation of configuration and code and the ability of
noncoders to easily modify the logging properties.
.. currentmodule:: logging
Note that the class names referenced in config files need to be either relative
to the logging module, or absolute values which can be resolved using normal
import mechanisms. Thus, you could use either
:class:`~logging.handlers.WatchedFileHandler` (relative to the logging module) or
``mypackage.mymodule.MyHandler`` (for a class defined in package ``mypackage``
and module ``mymodule``, where ``mypackage`` is available on the Python import
path).
In Python 2.7, a new means of configuring logging has been introduced, using
dictionaries to hold configuration information. This provides a superset of the
functionality of the config-file-based approach outlined above, and is the
recommended configuration method for new applications and deployments. Because
a Python dictionary is used to hold configuration information, and since you
can populate that dictionary using different means, you have more options for
configuration. For example, you can use a configuration file in JSON format,
or, if you have access to YAML processing functionality, a file in YAML
format, to populate the configuration dictionary. Or, of course, you can
construct the dictionary in Python code, receive it in pickled form over a
socket, or use whatever approach makes sense for your application.
Here's an example of the same configuration as above, in YAML format for
the new dictionary-based approach::
version: 1
formatters:
simple:
format: format=%(asctime)s - %(name)s - %(levelname)s - %(message)s
handlers:
console:
class: logging.StreamHandler
level: DEBUG
formatter: simple
stream: ext://sys.stdout
loggers:
simpleExample:
level: DEBUG
handlers: [console]
propagate: no
root:
level: DEBUG
handlers: [console]
For more information about logging using a dictionary, see
:ref:`logging-config-api`.
What happens if no configuration is provided
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
If no logging configuration is provided, it is possible to have a situation
where a logging event needs to be output, but no handlers can be found to
output the event. The behaviour of the logging package in these
circumstances is dependent on the Python version.
For Python 2.x, the behaviour is as follows:
* If *logging.raiseExceptions* is *False* (production mode), the event is
silently dropped.
* If *logging.raiseExceptions* is *True* (development mode), a message
'No handlers could be found for logger X.Y.Z' is printed once.
.. _library-config:
Configuring Logging for a Library
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
When developing a library which uses logging, you should take care to
document how the library uses logging - for example, the names of loggers
used. Some consideration also needs to be given to its logging configuration.
If the using application does not use logging, and library code makes logging
calls, then (as described in the previous section) events of severity
``WARNING`` and greater will be printed to ``sys.stderr``. This is regarded as
the best default behaviour.
If for some reason you *don't* want these messages printed in the absence of
any logging configuration, you can attach a do-nothing handler to the top-level
logger for your library. This avoids the message being printed, since a handler
will be always be found for the library's events: it just doesn't produce any
output. If the library user configures logging for application use, presumably
that configuration will add some handlers, and if levels are suitably
configured then logging calls made in library code will send output to those
handlers, as normal.
A do-nothing handler is included in the logging package:
:class:`~logging.NullHandler` (since Python 2.7). An instance of this handler
could be added to the top-level logger of the logging namespace used by the
library (*if* you want to prevent your library's logged events being output to
``sys.stderr`` in the absence of logging configuration). If all logging by a
library *foo* is done using loggers with names matching 'foo.x', 'foo.x.y',
etc. then the code::
import logging
logging.getLogger('foo').addHandler(logging.NullHandler())
should have the desired effect. If an organisation produces a number of
libraries, then the logger name specified can be 'orgname.foo' rather than
just 'foo'.
**PLEASE NOTE:** It is strongly advised that you *do not add any handlers other
than* :class:`~logging.NullHandler` *to your library's loggers*. This is
because the configuration of handlers is the prerogative of the application
developer who uses your library. The application developer knows their target
audience and what handlers are most appropriate for their application: if you
add handlers 'under the hood', you might well interfere with their ability to
carry out unit tests and deliver logs which suit their requirements.
Logging Levels
--------------
The numeric values of logging levels are given in the following table. These are
primarily of interest if you want to define your own levels, and need them to
have specific values relative to the predefined levels. If you define a level
with the same numeric value, it overwrites the predefined value; the predefined
name is lost.
+--------------+---------------+
| Level | Numeric value |
+==============+===============+
| ``CRITICAL`` | 50 |
+--------------+---------------+
| ``ERROR`` | 40 |
+--------------+---------------+
| ``WARNING`` | 30 |
+--------------+---------------+
| ``INFO`` | 20 |
+--------------+---------------+
| ``DEBUG`` | 10 |
+--------------+---------------+
| ``NOTSET`` | 0 |
+--------------+---------------+
Levels can also be associated with loggers, being set either by the developer or
through loading a saved logging configuration. When a logging method is called
on a logger, the logger compares its own level with the level associated with
the method call. If the logger's level is higher than the method call's, no
logging message is actually generated. This is the basic mechanism controlling
the verbosity of logging output.
Logging messages are encoded as instances of the :class:`~logging.LogRecord`
class. When a logger decides to actually log an event, a
:class:`~logging.LogRecord` instance is created from the logging message.
Logging messages are subjected to a dispatch mechanism through the use of
:dfn:`handlers`, which are instances of subclasses of the :class:`Handler`
class. Handlers are responsible for ensuring that a logged message (in the form
of a :class:`LogRecord`) ends up in a particular location (or set of locations)
which is useful for the target audience for that message (such as end users,
support desk staff, system administrators, developers). Handlers are passed
:class:`LogRecord` instances intended for particular destinations. Each logger
can have zero, one or more handlers associated with it (via the
:meth:`~Logger.addHandler` method of :class:`Logger`). In addition to any
handlers directly associated with a logger, *all handlers associated with all
ancestors of the logger* are called to dispatch the message (unless the
*propagate* flag for a logger is set to a false value, at which point the
passing to ancestor handlers stops).
Just as for loggers, handlers can have levels associated with them. A handler's
level acts as a filter in the same way as a logger's level does. If a handler
decides to actually dispatch an event, the :meth:`~Handler.emit` method is used
to send the message to its destination. Most user-defined subclasses of
:class:`Handler` will need to override this :meth:`~Handler.emit`.
.. _custom-levels:
Custom Levels
^^^^^^^^^^^^^
Defining your own levels is possible, but should not be necessary, as the
existing levels have been chosen on the basis of practical experience.
However, if you are convinced that you need custom levels, great care should
be exercised when doing this, and it is possibly *a very bad idea to define
custom levels if you are developing a library*. That's because if multiple
library authors all define their own custom levels, there is a chance that
the logging output from such multiple libraries used together will be
difficult for the using developer to control and/or interpret, because a
given numeric value might mean different things for different libraries.
.. _useful-handlers:
Useful Handlers
---------------
In addition to the base :class:`Handler` class, many useful subclasses are
provided:
#. :class:`StreamHandler` instances send messages to streams (file-like
objects).
#. :class:`FileHandler` instances send messages to disk files.
#. :class:`~handlers.BaseRotatingHandler` is the base class for handlers that
rotate log files at a certain point. It is not meant to be instantiated
directly. Instead, use :class:`~handlers.RotatingFileHandler` or
:class:`~handlers.TimedRotatingFileHandler`.
#. :class:`~handlers.RotatingFileHandler` instances send messages to disk
files, with support for maximum log file sizes and log file rotation.
#. :class:`~handlers.TimedRotatingFileHandler` instances send messages to
disk files, rotating the log file at certain timed intervals.
#. :class:`~handlers.SocketHandler` instances send messages to TCP/IP
sockets.
#. :class:`~handlers.DatagramHandler` instances send messages to UDP
sockets.
#. :class:`~handlers.SMTPHandler` instances send messages to a designated
email address.
#. :class:`~handlers.SysLogHandler` instances send messages to a Unix
syslog daemon, possibly on a remote machine.
#. :class:`~handlers.NTEventLogHandler` instances send messages to a
Windows NT/2000/XP event log.
#. :class:`~handlers.MemoryHandler` instances send messages to a buffer
in memory, which is flushed whenever specific criteria are met.
#. :class:`~handlers.HTTPHandler` instances send messages to an HTTP
server using either ``GET`` or ``POST`` semantics.
#. :class:`~handlers.WatchedFileHandler` instances watch the file they are
logging to. If the file changes, it is closed and reopened using the file
name. This handler is only useful on Unix-like systems; Windows does not
support the underlying mechanism used.
#. :class:`NullHandler` instances do nothing with error messages. They are used
by library developers who want to use logging, but want to avoid the 'No
handlers could be found for logger XXX' message which can be displayed if
the library user has not configured logging. See :ref:`library-config` for
more information.
.. versionadded:: 2.7
The :class:`NullHandler` class.
The :class:`NullHandler`, :class:`StreamHandler` and :class:`FileHandler`
classes are defined in the core logging package. The other handlers are
defined in a sub- module, :mod:`logging.handlers`. (There is also another
sub-module, :mod:`logging.config`, for configuration functionality.)
Logged messages are formatted for presentation through instances of the
:class:`Formatter` class. They are initialized with a format string suitable for
use with the % operator and a dictionary.
For formatting multiple messages in a batch, instances of
:class:`BufferingFormatter` can be used. In addition to the format string (which
is applied to each message in the batch), there is provision for header and
trailer format strings.
When filtering based on logger level and/or handler level is not enough,
instances of :class:`Filter` can be added to both :class:`Logger` and
:class:`Handler` instances (through their :meth:`addFilter` method). Before
deciding to process a message further, both loggers and handlers consult all
their filters for permission. If any filter returns a false value, the message
is not processed further.
The basic :class:`Filter` functionality allows filtering by specific logger
name. If this feature is used, messages sent to the named logger and its
children are allowed through the filter, and all others dropped.
.. _logging-exceptions:
Exceptions raised during logging
--------------------------------
The logging package is designed to swallow exceptions which occur while logging
in production. This is so that errors which occur while handling logging events
- such as logging misconfiguration, network or other similar errors - do not
cause the application using logging to terminate prematurely.
:class:`SystemExit` and :class:`KeyboardInterrupt` exceptions are never
swallowed. Other exceptions which occur during the :meth:`emit` method of a
:class:`Handler` subclass are passed to its :meth:`handleError` method.
The default implementation of :meth:`handleError` in :class:`Handler` checks
to see if a module-level variable, :data:`raiseExceptions`, is set. If set, a
traceback is printed to :data:`sys.stderr`. If not set, the exception is swallowed.
**Note:** The default value of :data:`raiseExceptions` is ``True``. This is because
during development, you typically want to be notified of any exceptions that
occur. It's advised that you set :data:`raiseExceptions` to ``False`` for production
usage.
.. currentmodule:: logging
.. _arbitrary-object-messages:
Using arbitrary objects as messages
-----------------------------------
In the preceding sections and examples, it has been assumed that the message
passed when logging the event is a string. However, this is not the only
possibility. You can pass an arbitrary object as a message, and its
:meth:`__str__` method will be called when the logging system needs to convert
it to a string representation. In fact, if you want to, you can avoid
computing a string representation altogether - for example, the
:class:`SocketHandler` emits an event by pickling it and sending it over the
wire.
Optimization
------------
Formatting of message arguments is deferred until it cannot be avoided.
However, computing the arguments passed to the logging method can also be
expensive, and you may want to avoid doing it if the logger will just throw
away your event. To decide what to do, you can call the :meth:`isEnabledFor`
method which takes a level argument and returns true if the event would be
created by the Logger for that level of call. You can write code like this::
if logger.isEnabledFor(logging.DEBUG):
logger.debug('Message with %s, %s', expensive_func1(),
expensive_func2())
so that if the logger's threshold is set above ``DEBUG``, the calls to
:func:`expensive_func1` and :func:`expensive_func2` are never made.
There are other optimizations which can be made for specific applications which
need more precise control over what logging information is collected. Here's a
list of things you can do to avoid processing during logging which you don't
need:
+-----------------------------------------------+----------------------------------------+
| What you don't want to collect | How to avoid collecting it |
+===============================================+========================================+
| Information about where calls were made from. | Set ``logging._srcfile`` to ``None``. |
+-----------------------------------------------+----------------------------------------+
| Threading information. | Set ``logging.logThreads`` to ``0``. |
+-----------------------------------------------+----------------------------------------+
| Process information. | Set ``logging.logProcesses`` to ``0``. |
+-----------------------------------------------+----------------------------------------+
Also note that the core logging module only includes the basic handlers. If
you don't import :mod:`logging.handlers` and :mod:`logging.config`, they won't
take up any memory.
.. seealso::
Module :mod:`logging`
API reference for the logging module.
Module :mod:`logging.config`
Configuration API for the logging module.
Module :mod:`logging.handlers`
Useful handlers included with the logging module.
:ref:`A logging cookbook <logging-cookbook>`
Doc/library/allos.rst
View file @ 5dbca9cc
......@@ -20,6 +20,8 @@ but they are available on most other systems as well. Here's an overview:
optparse.rst
getopt.rst
logging.rst
logging.config.rst
logging.handlers.rst
getpass.rst
curses.rst
curses.ascii.rst
......
Doc/library/logging.config.rst 0 → 100644
View file @ 5dbca9cc
:mod:`logging.config` --- Logging configuration
===============================================
.. module:: logging.config
:synopsis: Configuration of the logging module.
.. moduleauthor:: Vinay Sajip <vinay_sajip@red-dove.com>
.. sectionauthor:: Vinay Sajip <vinay_sajip@red-dove.com>
.. sidebar:: Important
This page contains only reference information. For tutorials,
please see
* :ref:`Basic Tutorial <logging-basic-tutorial>`
* :ref:`Advanced Tutorial <logging-advanced-tutorial>`
* :ref:`Logging Cookbook <logging-cookbook>`
This section describes the API for configuring the logging module.
.. _logging-config-api:
Configuration functions
^^^^^^^^^^^^^^^^^^^^^^^
The following functions configure the logging module. They are located in the
:mod:`logging.config` module. Their use is optional --- you can configure the
logging module using these functions or by making calls to the main API (defined
in :mod:`logging` itself) and defining handlers which are declared either in
:mod:`logging` or :mod:`logging.handlers`.
.. function:: dictConfig(config)
Takes the logging configuration from a dictionary. The contents of
this dictionary are described in :ref:`logging-config-dictschema`
below.
If an error is encountered during configuration, this function will
raise a :exc:`ValueError`, :exc:`TypeError`, :exc:`AttributeError`
or :exc:`ImportError` with a suitably descriptive message. The
following is a (possibly incomplete) list of conditions which will
raise an error:
* A ``level`` which is not a string or which is a string not
corresponding to an actual logging level.
* A ``propagate`` value which is not a boolean.
* An id which does not have a corresponding destination.
* A non-existent handler id found during an incremental call.
* An invalid logger name.
* Inability to resolve to an internal or external object.
Parsing is performed by the :class:`DictConfigurator` class, whose
constructor is passed the dictionary used for configuration, and
has a :meth:`configure` method. The :mod:`logging.config` module
has a callable attribute :attr:`dictConfigClass`
which is initially set to :class:`DictConfigurator`.
You can replace the value of :attr:`dictConfigClass` with a
suitable implementation of your own.
:func:`dictConfig` calls :attr:`dictConfigClass` passing
the specified dictionary, and then calls the :meth:`configure` method on
the returned object to put the configuration into effect::
def dictConfig(config):
dictConfigClass(config).configure()
For example, a subclass of :class:`DictConfigurator` could call
``DictConfigurator.__init__()`` in its own :meth:`__init__()`, then
set up custom prefixes which would be usable in the subsequent
:meth:`configure` call. :attr:`dictConfigClass` would be bound to
this new subclass, and then :func:`dictConfig` could be called exactly as
in the default, uncustomized state.
.. versionadded:: 2.7
.. function:: fileConfig(fname[, defaults])
Reads the logging configuration from a :mod:`configparser`\-format file named
*fname*. This function can be called several times from an application,
allowing an end user to select from various pre-canned
configurations (if the developer provides a mechanism to present the choices
and load the chosen configuration). Defaults to be passed to the ConfigParser
can be specified in the *defaults* argument.
.. function:: listen(port=DEFAULT_LOGGING_CONFIG_PORT)
Starts up a socket server on the specified port, and listens for new
configurations. If no port is specified, the module's default
:const:`DEFAULT_LOGGING_CONFIG_PORT` is used. Logging configurations will be
sent as a file suitable for processing by :func:`fileConfig`. Returns a
:class:`Thread` instance on which you can call :meth:`start` to start the
server, and which you can :meth:`join` when appropriate. To stop the server,
call :func:`stopListening`.
To send a configuration to the socket, read in the configuration file and
send it to the socket as a string of bytes preceded by a four-byte length
string packed in binary using ``struct.pack('>L', n)``.
.. function:: stopListening()
Stops the listening server which was created with a call to :func:`listen`.
This is typically called before calling :meth:`join` on the return value from
:func:`listen`.
.. _logging-config-dictschema:
Configuration dictionary schema
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Describing a logging configuration requires listing the various
objects to create and the connections between them; for example, you
may create a handler named 'console' and then say that the logger
named 'startup' will send its messages to the 'console' handler.
These objects aren't limited to those provided by the :mod:`logging`
module because you might write your own formatter or handler class.
The parameters to these classes may also need to include external
objects such as ``sys.stderr``. The syntax for describing these
objects and connections is defined in :ref:`logging-config-dict-connections`
below.
Dictionary Schema Details
"""""""""""""""""""""""""
The dictionary passed to :func:`dictConfig` must contain the following
keys:
* *version* - to be set to an integer value representing the schema
version. The only valid value at present is 1, but having this key
allows the schema to evolve while still preserving backwards
compatibility.
All other keys are optional, but if present they will be interpreted
as described below. In all cases below where a 'configuring dict' is
mentioned, it will be checked for the special ``'()'`` key to see if a
custom instantiation is required. If so, the mechanism described in
:ref:`logging-config-dict-userdef` below is used to create an instance;
otherwise, the context is used to determine what to instantiate.
* *formatters* - the corresponding value will be a dict in which each
key is a formatter id and each value is a dict describing how to
configure the corresponding Formatter instance.
The configuring dict is searched for keys ``format`` and ``datefmt``
(with defaults of ``None``) and these are used to construct a
:class:`logging.Formatter` instance.
* *filters* - the corresponding value will be a dict in which each key
is a filter id and each value is a dict describing how to configure
the corresponding Filter instance.
The configuring dict is searched for the key ``name`` (defaulting to the
empty string) and this is used to construct a :class:`logging.Filter`
instance.
* *handlers* - the corresponding value will be a dict in which each
key is a handler id and each value is a dict describing how to
configure the corresponding Handler instance.
The configuring dict is searched for the following keys:
* ``class`` (mandatory). This is the fully qualified name of the
handler class.
* ``level`` (optional). The level of the handler.
* ``formatter`` (optional). The id of the formatter for this
handler.
* ``filters`` (optional). A list of ids of the filters for this
handler.
All *other* keys are passed through as keyword arguments to the
handler's constructor. For example, given the snippet::
handlers:
console:
class : logging.StreamHandler
formatter: brief
level : INFO
filters: [allow_foo]
stream : ext://sys.stdout
file:
class : logging.handlers.RotatingFileHandler
formatter: precise
filename: logconfig.log
maxBytes: 1024
backupCount: 3
the handler with id ``console`` is instantiated as a
:class:`logging.StreamHandler`, using ``sys.stdout`` as the underlying
stream. The handler with id ``file`` is instantiated as a
:class:`logging.handlers.RotatingFileHandler` with the keyword arguments
``filename='logconfig.log', maxBytes=1024, backupCount=3``.
* *loggers* - the corresponding value will be a dict in which each key
is a logger name and each value is a dict describing how to
configure the corresponding Logger instance.
The configuring dict is searched for the following keys:
* ``level`` (optional). The level of the logger.
* ``propagate`` (optional). The propagation setting of the logger.
* ``filters`` (optional). A list of ids of the filters for this
logger.
* ``handlers`` (optional). A list of ids of the handlers for this
logger.
The specified loggers will be configured according to the level,
propagation, filters and handlers specified.
* *root* - this will be the configuration for the root logger.
Processing of the configuration will be as for any logger, except
that the ``propagate`` setting will not be applicable.
* *incremental* - whether the configuration is to be interpreted as
incremental to the existing configuration. This value defaults to
``False``, which means that the specified configuration replaces the
existing configuration with the same semantics as used by the
existing :func:`fileConfig` API.
If the specified value is ``True``, the configuration is processed
as described in the section on :ref:`logging-config-dict-incremental`.
* *disable_existing_loggers* - whether any existing loggers are to be
disabled. This setting mirrors the parameter of the same name in
:func:`fileConfig`. If absent, this parameter defaults to ``True``.
This value is ignored if *incremental* is ``True``.
.. _logging-config-dict-incremental:
Incremental Configuration
"""""""""""""""""""""""""
It is difficult to provide complete flexibility for incremental
configuration. For example, because objects such as filters
and formatters are anonymous, once a configuration is set up, it is
not possible to refer to such anonymous objects when augmenting a
configuration.
Furthermore, there is not a compelling case for arbitrarily altering
the object graph of loggers, handlers, filters, formatters at
run-time, once a configuration is set up; the verbosity of loggers and
handlers can be controlled just by setting levels (and, in the case of
loggers, propagation flags). Changing the object graph arbitrarily in
a safe way is problematic in a multi-threaded environment; while not
impossible, the benefits are not worth the complexity it adds to the
implementation.
Thus, when the ``incremental`` key of a configuration dict is present
and is ``True``, the system will completely ignore any ``formatters`` and
``filters`` entries, and process only the ``level``
settings in the ``handlers`` entries, and the ``level`` and
``propagate`` settings in the ``loggers`` and ``root`` entries.
Using a value in the configuration dict lets configurations to be sent
over the wire as pickled dicts to a socket listener. Thus, the logging
verbosity of a long-running application can be altered over time with
no need to stop and restart the application.
.. _logging-config-dict-connections:
Object connections
""""""""""""""""""
The schema describes a set of logging objects - loggers,
handlers, formatters, filters - which are connected to each other in
an object graph. Thus, the schema needs to represent connections
between the objects. For example, say that, once configured, a
particular logger has attached to it a particular handler. For the
purposes of this discussion, we can say that the logger represents the
source, and the handler the destination, of a connection between the
two. Of course in the configured objects this is represented by the
logger holding a reference to the handler. In the configuration dict,
this is done by giving each destination object an id which identifies
it unambiguously, and then using the id in the source object's
configuration to indicate that a connection exists between the source
and the destination object with that id.
So, for example, consider the following YAML snippet::
formatters:
brief:
# configuration for formatter with id 'brief' goes here
precise:
# configuration for formatter with id 'precise' goes here
handlers:
h1: #This is an id
# configuration of handler with id 'h1' goes here
formatter: brief
h2: #This is another id
# configuration of handler with id 'h2' goes here
formatter: precise
loggers:
foo.bar.baz:
# other configuration for logger 'foo.bar.baz'
handlers: [h1, h2]
(Note: YAML used here because it's a little more readable than the
equivalent Python source form for the dictionary.)
The ids for loggers are the logger names which would be used
programmatically to obtain a reference to those loggers, e.g.
``foo.bar.baz``. The ids for Formatters and Filters can be any string
value (such as ``brief``, ``precise`` above) and they are transient,
in that they are only meaningful for processing the configuration
dictionary and used to determine connections between objects, and are
not persisted anywhere when the configuration call is complete.
The above snippet indicates that logger named ``foo.bar.baz`` should
have two handlers attached to it, which are described by the handler
ids ``h1`` and ``h2``. The formatter for ``h1`` is that described by id
``brief``, and the formatter for ``h2`` is that described by id
``precise``.
.. _logging-config-dict-userdef:
User-defined objects
""""""""""""""""""""
The schema supports user-defined objects for handlers, filters and
formatters. (Loggers do not need to have different types for
different instances, so there is no support in this configuration
schema for user-defined logger classes.)
Objects to be configured are described by dictionaries
which detail their configuration. In some places, the logging system
will be able to infer from the context how an object is to be
instantiated, but when a user-defined object is to be instantiated,
the system will not know how to do this. In order to provide complete
flexibility for user-defined object instantiation, the user needs
to provide a 'factory' - a callable which is called with a
configuration dictionary and which returns the instantiated object.
This is signalled by an absolute import path to the factory being
made available under the special key ``'()'``. Here's a concrete
example::
formatters:
brief:
format: '%(message)s'
default:
format: '%(asctime)s %(levelname)-8s %(name)-15s %(message)s'
datefmt: '%Y-%m-%d %H:%M:%S'
custom:
(): my.package.customFormatterFactory
bar: baz
spam: 99.9
answer: 42
The above YAML snippet defines three formatters. The first, with id
``brief``, is a standard :class:`logging.Formatter` instance with the
specified format string. The second, with id ``default``, has a
longer format and also defines the time format explicitly, and will
result in a :class:`logging.Formatter` initialized with those two format
strings. Shown in Python source form, the ``brief`` and ``default``
formatters have configuration sub-dictionaries::
{
'format' : '%(message)s'
}
and::
{
'format' : '%(asctime)s %(levelname)-8s %(name)-15s %(message)s',
'datefmt' : '%Y-%m-%d %H:%M:%S'
}
respectively, and as these dictionaries do not contain the special key
``'()'``, the instantiation is inferred from the context: as a result,
standard :class:`logging.Formatter` instances are created. The
configuration sub-dictionary for the third formatter, with id
``custom``, is::
{
'()' : 'my.package.customFormatterFactory',
'bar' : 'baz',
'spam' : 99.9,
'answer' : 42
}
and this contains the special key ``'()'``, which means that
user-defined instantiation is wanted. In this case, the specified
factory callable will be used. If it is an actual callable it will be
used directly - otherwise, if you specify a string (as in the example)
the actual callable will be located using normal import mechanisms.
The callable will be called with the **remaining** items in the
configuration sub-dictionary as keyword arguments. In the above
example, the formatter with id ``custom`` will be assumed to be
returned by the call::
my.package.customFormatterFactory(bar='baz', spam=99.9, answer=42)
The key ``'()'`` has been used as the special key because it is not a
valid keyword parameter name, and so will not clash with the names of
the keyword arguments used in the call. The ``'()'`` also serves as a
mnemonic that the corresponding value is a callable.
.. _logging-config-dict-externalobj:
Access to external objects
""""""""""""""""""""""""""
There are times where a configuration needs to refer to objects
external to the configuration, for example ``sys.stderr``. If the
configuration dict is constructed using Python code, this is
straightforward, but a problem arises when the configuration is
provided via a text file (e.g. JSON, YAML). In a text file, there is
no standard way to distinguish ``sys.stderr`` from the literal string
``'sys.stderr'``. To facilitate this distinction, the configuration
system looks for certain special prefixes in string values and
treat them specially. For example, if the literal string
``'ext://sys.stderr'`` is provided as a value in the configuration,
then the ``ext://`` will be stripped off and the remainder of the
value processed using normal import mechanisms.
The handling of such prefixes is done in a way analogous to protocol
handling: there is a generic mechanism to look for prefixes which
match the regular expression ``^(?P<prefix>[a-z]+)://(?P<suffix>.*)$``
whereby, if the ``prefix`` is recognised, the ``suffix`` is processed
in a prefix-dependent manner and the result of the processing replaces
the string value. If the prefix is not recognised, then the string
value will be left as-is.
.. _logging-config-dict-internalobj:
Access to internal objects
""""""""""""""""""""""""""
As well as external objects, there is sometimes also a need to refer
to objects in the configuration. This will be done implicitly by the
configuration system for things that it knows about. For example, the
string value ``'DEBUG'`` for a ``level`` in a logger or handler will
automatically be converted to the value ``logging.DEBUG``, and the
``handlers``, ``filters`` and ``formatter`` entries will take an
object id and resolve to the appropriate destination object.
However, a more generic mechanism is needed for user-defined
objects which are not known to the :mod:`logging` module. For
example, consider :class:`logging.handlers.MemoryHandler`, which takes
a ``target`` argument which is another handler to delegate to. Since
the system already knows about this class, then in the configuration,
the given ``target`` just needs to be the object id of the relevant
target handler, and the system will resolve to the handler from the
id. If, however, a user defines a ``my.package.MyHandler`` which has
an ``alternate`` handler, the configuration system would not know that
the ``alternate`` referred to a handler. To cater for this, a generic
resolution system allows the user to specify::
handlers:
file:
# configuration of file handler goes here
custom:
(): my.package.MyHandler
alternate: cfg://handlers.file
The literal string ``'cfg://handlers.file'`` will be resolved in an
analogous way to strings with the ``ext://`` prefix, but looking
in the configuration itself rather than the import namespace. The
mechanism allows access by dot or by index, in a similar way to
that provided by ``str.format``. Thus, given the following snippet::
handlers:
email:
class: logging.handlers.SMTPHandler
mailhost: localhost
fromaddr: my_app@domain.tld
toaddrs:
- support_team@domain.tld
- dev_team@domain.tld
subject: Houston, we have a problem.
in the configuration, the string ``'cfg://handlers'`` would resolve to
the dict with key ``handlers``, the string ``'cfg://handlers.email``
would resolve to the dict with key ``email`` in the ``handlers`` dict,
and so on. The string ``'cfg://handlers.email.toaddrs[1]`` would
resolve to ``'dev_team.domain.tld'`` and the string
``'cfg://handlers.email.toaddrs[0]'`` would resolve to the value
``'support_team@domain.tld'``. The ``subject`` value could be accessed
using either ``'cfg://handlers.email.subject'`` or, equivalently,
``'cfg://handlers.email[subject]'``. The latter form only needs to be
used if the key contains spaces or non-alphanumeric characters. If an
index value consists only of decimal digits, access will be attempted
using the corresponding integer value, falling back to the string
value if needed.
Given a string ``cfg://handlers.myhandler.mykey.123``, this will
resolve to ``config_dict['handlers']['myhandler']['mykey']['123']``.
If the string is specified as ``cfg://handlers.myhandler.mykey[123]``,
the system will attempt to retrieve the value from
``config_dict['handlers']['myhandler']['mykey'][123]``, and fall back
to ``config_dict['handlers']['myhandler']['mykey']['123']`` if that
fails.
.. _logging-config-fileformat:
Configuration file format
^^^^^^^^^^^^^^^^^^^^^^^^^
The configuration file format understood by :func:`fileConfig` is based on
:mod:`configparser` functionality. The file must contain sections called
``[loggers]``, ``[handlers]`` and ``[formatters]`` which identify by name the
entities of each type which are defined in the file. For each such entity, there
is a separate section which identifies how that entity is configured. Thus, for
a logger named ``log01`` in the ``[loggers]`` section, the relevant
configuration details are held in a section ``[logger_log01]``. Similarly, a
handler called ``hand01`` in the ``[handlers]`` section will have its
configuration held in a section called ``[handler_hand01]``, while a formatter
called ``form01`` in the ``[formatters]`` section will have its configuration
specified in a section called ``[formatter_form01]``. The root logger
configuration must be specified in a section called ``[logger_root]``.
Examples of these sections in the file are given below. ::
[loggers]
keys=root,log02,log03,log04,log05,log06,log07
[handlers]
keys=hand01,hand02,hand03,hand04,hand05,hand06,hand07,hand08,hand09
[formatters]
keys=form01,form02,form03,form04,form05,form06,form07,form08,form09
The root logger must specify a level and a list of handlers. An example of a
root logger section is given below. ::
[logger_root]
level=NOTSET
handlers=hand01
The ``level`` entry can be one of ``DEBUG, INFO, WARNING, ERROR, CRITICAL`` or
``NOTSET``. For the root logger only, ``NOTSET`` means that all messages will be
logged. Level values are :func:`eval`\ uated in the context of the ``logging``
package's namespace.
The ``handlers`` entry is a comma-separated list of handler names, which must
appear in the ``[handlers]`` section. These names must appear in the
``[handlers]`` section and have corresponding sections in the configuration
file.
For loggers other than the root logger, some additional information is required.
This is illustrated by the following example. ::
[logger_parser]
level=DEBUG
handlers=hand01
propagate=1
qualname=compiler.parser
The ``level`` and ``handlers`` entries are interpreted as for the root logger,
except that if a non-root logger's level is specified as ``NOTSET``, the system
consults loggers higher up the hierarchy to determine the effective level of the
logger. The ``propagate`` entry is set to 1 to indicate that messages must
propagate to handlers higher up the logger hierarchy from this logger, or 0 to
indicate that messages are **not** propagated to handlers up the hierarchy. The
``qualname`` entry is the hierarchical channel name of the logger, that is to
say the name used by the application to get the logger.
Sections which specify handler configuration are exemplified by the following.
::
[handler_hand01]
class=StreamHandler
level=NOTSET
formatter=form01
args=(sys.stdout,)
The ``class`` entry indicates the handler's class (as determined by :func:`eval`
in the ``logging`` package's namespace). The ``level`` is interpreted as for
loggers, and ``NOTSET`` is taken to mean 'log everything'.
.. versionchanged:: 2.6
Added support for resolving the handler’s class as a dotted module and
class name.
The ``formatter`` entry indicates the key name of the formatter for this
handler. If blank, a default formatter (``logging._defaultFormatter``) is used.
If a name is specified, it must appear in the ``[formatters]`` section and have
a corresponding section in the configuration file.
The ``args`` entry, when :func:`eval`\ uated in the context of the ``logging``
package's namespace, is the list of arguments to the constructor for the handler
class. Refer to the constructors for the relevant handlers, or to the examples
below, to see how typical entries are constructed. ::
[handler_hand02]
class=FileHandler
level=DEBUG
formatter=form02
args=('python.log', 'w')
[handler_hand03]
class=handlers.SocketHandler
level=INFO
formatter=form03
args=('localhost', handlers.DEFAULT_TCP_LOGGING_PORT)
[handler_hand04]
class=handlers.DatagramHandler
level=WARN
formatter=form04
args=('localhost', handlers.DEFAULT_UDP_LOGGING_PORT)
[handler_hand05]
class=handlers.SysLogHandler
level=ERROR
formatter=form05
args=(('localhost', handlers.SYSLOG_UDP_PORT), handlers.SysLogHandler.LOG_USER)
[handler_hand06]
class=handlers.NTEventLogHandler
level=CRITICAL
formatter=form06
args=('Python Application', '', 'Application')
[handler_hand07]
class=handlers.SMTPHandler
level=WARN
formatter=form07
args=('localhost', 'from@abc', ['user1@abc', 'user2@xyz'], 'Logger Subject')
[handler_hand08]
class=handlers.MemoryHandler
level=NOTSET
formatter=form08
target=
args=(10, ERROR)
[handler_hand09]
class=handlers.HTTPHandler
level=NOTSET
formatter=form09
args=('localhost:9022', '/log', 'GET')
Sections which specify formatter configuration are typified by the following. ::
[formatter_form01]
format=F1 %(asctime)s %(levelname)s %(message)s
datefmt=
class=logging.Formatter
The ``format`` entry is the overall format string, and the ``datefmt`` entry is
the :func:`strftime`\ -compatible date/time format string. If empty, the
package substitutes ISO8601 format date/times, which is almost equivalent to
specifying the date format string ``'%Y-%m-%d %H:%M:%S'``. The ISO8601 format
also specifies milliseconds, which are appended to the result of using the above
format string, with a comma separator. An example time in ISO8601 format is
``2003-01-23 00:29:50,411``.
The ``class`` entry is optional. It indicates the name of the formatter's class
(as a dotted module and class name.) This option is useful for instantiating a
:class:`Formatter` subclass. Subclasses of :class:`Formatter` can present
exception tracebacks in an expanded or condensed format.
.. seealso::
Module :mod:`logging`
API reference for the logging module.
Module :mod:`logging.handlers`
Useful handlers included with the logging module.
Doc/library/logging.handlers.rst 0 → 100644
View file @ 5dbca9cc
:mod:`logging.handlers` --- Logging handlers
============================================
.. module:: logging.handlers
:synopsis: Handlers for the logging module.
.. moduleauthor:: Vinay Sajip <vinay_sajip@red-dove.com>
.. sectionauthor:: Vinay Sajip <vinay_sajip@red-dove.com>
.. sidebar:: Important
This page contains only reference information. For tutorials,
please see
* :ref:`Basic Tutorial <logging-basic-tutorial>`
* :ref:`Advanced Tutorial <logging-advanced-tutorial>`
* :ref:`Logging Cookbook <logging-cookbook>`
.. currentmodule:: logging
The following useful handlers are provided in the package. Note that three of
the handlers (:class:`StreamHandler`, :class:`FileHandler` and
:class:`NullHandler`) are actually defined in the :mod:`logging` module itself,
but have been documented here along with the other handlers.
.. _stream-handler:
StreamHandler
^^^^^^^^^^^^^
The :class:`StreamHandler` class, located in the core :mod:`logging` package,
sends logging output to streams such as *sys.stdout*, *sys.stderr* or any
file-like object (or, more precisely, any object which supports :meth:`write`
and :meth:`flush` methods).
.. class:: StreamHandler(stream=None)
Returns a new instance of the :class:`StreamHandler` class. If *stream* is
specified, the instance will use it for logging output; otherwise, *sys.stderr*
will be used.
.. method:: emit(record)
If a formatter is specified, it is used to format the record. The record
is then written to the stream with a newline terminator. If exception
information is present, it is formatted using
:func:`traceback.print_exception` and appended to the stream.
.. method:: flush()
Flushes the stream by calling its :meth:`flush` method. Note that the
:meth:`close` method is inherited from :class:`Handler` and so does
no output, so an explicit :meth:`flush` call may be needed at times.
.. _file-handler:
FileHandler
^^^^^^^^^^^
The :class:`FileHandler` class, located in the core :mod:`logging` package,
sends logging output to a disk file. It inherits the output functionality from
:class:`StreamHandler`.
.. class:: FileHandler(filename, mode='a', encoding=None, delay=False)
Returns a new instance of the :class:`FileHandler` class. The specified file is
opened and used as the stream for logging. If *mode* is not specified,
:const:`'a'` is used. If *encoding* is not *None*, it is used to open the file
with that encoding. If *delay* is true, then file opening is deferred until the
first call to :meth:`emit`. By default, the file grows indefinitely.
.. versionchanged:: 2.6
*delay* was added.
.. method:: close()
Closes the file.
.. method:: emit(record)
Outputs the record to the file.
.. _null-handler:
NullHandler
^^^^^^^^^^^
.. versionadded:: 2.7
The :class:`NullHandler` class, located in the core :mod:`logging` package,
does not do any formatting or output. It is essentially a 'no-op' handler
for use by library developers.
.. class:: NullHandler()
Returns a new instance of the :class:`NullHandler` class.
.. method:: emit(record)
This method does nothing.
.. method:: handle(record)
This method does nothing.
.. method:: createLock()
This method returns ``None`` for the lock, since there is no
underlying I/O to which access needs to be serialized.
See :ref:`library-config` for more information on how to use
:class:`NullHandler`.
.. _watched-file-handler:
WatchedFileHandler
^^^^^^^^^^^^^^^^^^
.. currentmodule:: logging.handlers
.. versionadded:: 2.6
The :class:`WatchedFileHandler` class, located in the :mod:`logging.handlers`
module, is a :class:`FileHandler` which watches the file it is logging to. If
the file changes, it is closed and reopened using the file name.
A file change can happen because of usage of programs such as *newsyslog* and
*logrotate* which perform log file rotation. This handler, intended for use
under Unix/Linux, watches the file to see if it has changed since the last emit.
(A file is deemed to have changed if its device or inode have changed.) If the
file has changed, the old file stream is closed, and the file opened to get a
new stream.
This handler is not appropriate for use under Windows, because under Windows
open log files cannot be moved or renamed - logging opens the files with
exclusive locks - and so there is no need for such a handler. Furthermore,
*ST_INO* is not supported under Windows; :func:`stat` always returns zero for
this value.
.. class:: WatchedFileHandler(filename[,mode[, encoding[, delay]]])
Returns a new instance of the :class:`WatchedFileHandler` class. The specified
file is opened and used as the stream for logging. If *mode* is not specified,
:const:`'a'` is used. If *encoding* is not *None*, it is used to open the file
with that encoding. If *delay* is true, then file opening is deferred until the
first call to :meth:`emit`. By default, the file grows indefinitely.
.. method:: emit(record)
Outputs the record to the file, but first checks to see if the file has
changed. If it has, the existing stream is flushed and closed and the
file opened again, before outputting the record to the file.
.. _rotating-file-handler:
RotatingFileHandler
^^^^^^^^^^^^^^^^^^^
The :class:`RotatingFileHandler` class, located in the :mod:`logging.handlers`
module, supports rotation of disk log files.
.. class:: RotatingFileHandler(filename, mode='a', maxBytes=0, backupCount=0, encoding=None, delay=0)
Returns a new instance of the :class:`RotatingFileHandler` class. The specified
file is opened and used as the stream for logging. If *mode* is not specified,
``'a'`` is used. If *encoding* is not *None*, it is used to open the file
with that encoding. If *delay* is true, then file opening is deferred until the
first call to :meth:`emit`. By default, the file grows indefinitely.
You can use the *maxBytes* and *backupCount* values to allow the file to
:dfn:`rollover` at a predetermined size. When the size is about to be exceeded,
the file is closed and a new file is silently opened for output. Rollover occurs
whenever the current log file is nearly *maxBytes* in length; if *maxBytes* is
zero, rollover never occurs. If *backupCount* is non-zero, the system will save
old log files by appending the extensions '.1', '.2' etc., to the filename. For
example, with a *backupCount* of 5 and a base file name of :file:`app.log`, you
would get :file:`app.log`, :file:`app.log.1`, :file:`app.log.2`, up to
:file:`app.log.5`. The file being written to is always :file:`app.log`. When
this file is filled, it is closed and renamed to :file:`app.log.1`, and if files
:file:`app.log.1`, :file:`app.log.2`, etc. exist, then they are renamed to
:file:`app.log.2`, :file:`app.log.3` etc. respectively.
.. versionchanged:: 2.6
*delay* was added.
.. method:: doRollover()
Does a rollover, as described above.
.. method:: emit(record)
Outputs the record to the file, catering for rollover as described
previously.
.. _timed-rotating-file-handler:
TimedRotatingFileHandler
^^^^^^^^^^^^^^^^^^^^^^^^
The :class:`TimedRotatingFileHandler` class, located in the
:mod:`logging.handlers` module, supports rotation of disk log files at certain
timed intervals.
.. class:: TimedRotatingFileHandler(filename, when='h', interval=1, backupCount=0, encoding=None, delay=False, utc=False)
Returns a new instance of the :class:`TimedRotatingFileHandler` class. The
specified file is opened and used as the stream for logging. On rotating it also
sets the filename suffix. Rotating happens based on the product of *when* and
*interval*.
You can use the *when* to specify the type of *interval*. The list of possible
values is below. Note that they are not case sensitive.
+----------------+-----------------------+
| Value | Type of interval |
+================+=======================+
| ``'S'`` | Seconds |
+----------------+-----------------------+
| ``'M'`` | Minutes |
+----------------+-----------------------+
| ``'H'`` | Hours |
+----------------+-----------------------+
| ``'D'`` | Days |
+----------------+-----------------------+
| ``'W'`` | Week day (0=Monday) |
+----------------+-----------------------+
| ``'midnight'`` | Roll over at midnight |
+----------------+-----------------------+
The system will save old log files by appending extensions to the filename.
The extensions are date-and-time based, using the strftime format
``%Y-%m-%d_%H-%M-%S`` or a leading portion thereof, depending on the
rollover interval.
When computing the next rollover time for the first time (when the handler
is created), the last modification time of an existing log file, or else
the current time, is used to compute when the next rotation will occur.
If the *utc* argument is true, times in UTC will be used; otherwise
local time is used.
If *backupCount* is nonzero, at most *backupCount* files
will be kept, and if more would be created when rollover occurs, the oldest
one is deleted. The deletion logic uses the interval to determine which
files to delete, so changing the interval may leave old files lying around.
If *delay* is true, then file opening is deferred until the first call to
:meth:`emit`.
.. versionchanged:: 2.6
*delay* was added.
.. versionchanged:: 2.7
*utc* was added.
.. method:: doRollover()
Does a rollover, as described above.
.. method:: emit(record)
Outputs the record to the file, catering for rollover as described above.
.. _socket-handler:
SocketHandler
^^^^^^^^^^^^^
The :class:`SocketHandler` class, located in the :mod:`logging.handlers` module,
sends logging output to a network socket. The base class uses a TCP socket.
.. class:: SocketHandler(host, port)
Returns a new instance of the :class:`SocketHandler` class intended to
communicate with a remote machine whose address is given by *host* and *port*.
.. method:: close()
Closes the socket.
.. method:: emit()
Pickles the record's attribute dictionary and writes it to the socket in
binary format. If there is an error with the socket, silently drops the
packet. If the connection was previously lost, re-establishes the
connection. To unpickle the record at the receiving end into a
:class:`LogRecord`, use the :func:`makeLogRecord` function.
.. method:: handleError()
Handles an error which has occurred during :meth:`emit`. The most likely
cause is a lost connection. Closes the socket so that we can retry on the
next event.
.. method:: makeSocket()
This is a factory method which allows subclasses to define the precise
type of socket they want. The default implementation creates a TCP socket
(:const:`socket.SOCK_STREAM`).
.. method:: makePickle(record)
Pickles the record's attribute dictionary in binary format with a length
prefix, and returns it ready for transmission across the socket.
Note that pickles aren't completely secure. If you are concerned about
security, you may want to override this method to implement a more secure
mechanism. For example, you can sign pickles using HMAC and then verify
them on the receiving end, or alternatively you can disable unpickling of
global objects on the receiving end.
.. method:: send(packet)
Send a pickled string *packet* to the socket. This function allows for
partial sends which can happen when the network is busy.
.. method:: createSocket()
Tries to create a socket; on failure, uses an exponential back-off
algorithm. On intial failure, the handler will drop the message it was
trying to send. When subsequent messages are handled by the same
instance, it will not try connecting until some time has passed. The
default parameters are such that the initial delay is one second, and if
after that delay the connection still can't be made, the handler will
double the delay each time up to a maximum of 30 seconds.
This behaviour is controlled by the following handler attributes:
* ``retryStart`` (initial delay, defaulting to 1.0 seconds).
* ``retryFactor`` (multiplier, defaulting to 2.0).
* ``retryMax`` (maximum delay, defaulting to 30.0 seconds).
This means that if the remote listener starts up *after* the handler has
been used, you could lose messages (since the handler won't even attempt
a connection until the delay has elapsed, but just silently drop messages
during the delay period).
.. _datagram-handler:
DatagramHandler
^^^^^^^^^^^^^^^
The :class:`DatagramHandler` class, located in the :mod:`logging.handlers`
module, inherits from :class:`SocketHandler` to support sending logging messages
over UDP sockets.
.. class:: DatagramHandler(host, port)
Returns a new instance of the :class:`DatagramHandler` class intended to
communicate with a remote machine whose address is given by *host* and *port*.
.. method:: emit()
Pickles the record's attribute dictionary and writes it to the socket in
binary format. If there is an error with the socket, silently drops the
packet. To unpickle the record at the receiving end into a
:class:`LogRecord`, use the :func:`makeLogRecord` function.
.. method:: makeSocket()
The factory method of :class:`SocketHandler` is here overridden to create
a UDP socket (:const:`socket.SOCK_DGRAM`).
.. method:: send(s)
Send a pickled string to a socket.
.. _syslog-handler:
SysLogHandler
^^^^^^^^^^^^^
The :class:`SysLogHandler` class, located in the :mod:`logging.handlers` module,
supports sending logging messages to a remote or local Unix syslog.
.. class:: SysLogHandler(address=('localhost', SYSLOG_UDP_PORT), facility=LOG_USER, socktype=socket.SOCK_DGRAM)
Returns a new instance of the :class:`SysLogHandler` class intended to
communicate with a remote Unix machine whose address is given by *address* in
the form of a ``(host, port)`` tuple. If *address* is not specified,
``('localhost', 514)`` is used. The address is used to open a socket. An
alternative to providing a ``(host, port)`` tuple is providing an address as a
string, for example '/dev/log'. In this case, a Unix domain socket is used to
send the message to the syslog. If *facility* is not specified,
:const:`LOG_USER` is used. The type of socket opened depends on the
*socktype* argument, which defaults to :const:`socket.SOCK_DGRAM` and thus
opens a UDP socket. To open a TCP socket (for use with the newer syslog
daemons such as rsyslog), specify a value of :const:`socket.SOCK_STREAM`.
Note that if your server is not listening on UDP port 514,
:class:`SysLogHandler` may appear not to work. In that case, check what
address you should be using for a domain socket - it's system dependent.
For example, on Linux it's usually '/dev/log' but on OS/X it's
'/var/run/syslog'. You'll need to check your platform and use the
appropriate address (you may need to do this check at runtime if your
application needs to run on several platforms). On Windows, you pretty
much have to use the UDP option.
.. versionchanged:: 2.7
*socktype* was added.
.. method:: close()
Closes the socket to the remote host.
.. method:: emit(record)
The record is formatted, and then sent to the syslog server. If exception
information is present, it is *not* sent to the server.
.. method:: encodePriority(facility, priority)
Encodes the facility and priority into an integer. You can pass in strings
or integers - if strings are passed, internal mapping dictionaries are
used to convert them to integers.
The symbolic ``LOG_`` values are defined in :class:`SysLogHandler` and
mirror the values defined in the ``sys/syslog.h`` header file.
**Priorities**
+--------------------------+---------------+
| Name (string) | Symbolic value|
+==========================+===============+
| ``alert`` | LOG_ALERT |
+--------------------------+---------------+
| ``crit`` or ``critical`` | LOG_CRIT |
+--------------------------+---------------+
| ``debug`` | LOG_DEBUG |
+--------------------------+---------------+
| ``emerg`` or ``panic`` | LOG_EMERG |
+--------------------------+---------------+
| ``err`` or ``error`` | LOG_ERR |
+--------------------------+---------------+
| ``info`` | LOG_INFO |
+--------------------------+---------------+
| ``notice`` | LOG_NOTICE |
+--------------------------+---------------+
| ``warn`` or ``warning`` | LOG_WARNING |
+--------------------------+---------------+
**Facilities**
+---------------+---------------+
| Name (string) | Symbolic value|
+===============+===============+
| ``auth`` | LOG_AUTH |
+---------------+---------------+
| ``authpriv`` | LOG_AUTHPRIV |
+---------------+---------------+
| ``cron`` | LOG_CRON |
+---------------+---------------+
| ``daemon`` | LOG_DAEMON |
+---------------+---------------+
| ``ftp`` | LOG_FTP |
+---------------+---------------+
| ``kern`` | LOG_KERN |
+---------------+---------------+
| ``lpr`` | LOG_LPR |
+---------------+---------------+
| ``mail`` | LOG_MAIL |
+---------------+---------------+
| ``news`` | LOG_NEWS |
+---------------+---------------+
| ``syslog`` | LOG_SYSLOG |
+---------------+---------------+
| ``user`` | LOG_USER |
+---------------+---------------+
| ``uucp`` | LOG_UUCP |
+---------------+---------------+
| ``local0`` | LOG_LOCAL0 |
+---------------+---------------+
| ``local1`` | LOG_LOCAL1 |
+---------------+---------------+
| ``local2`` | LOG_LOCAL2 |
+---------------+---------------+
| ``local3`` | LOG_LOCAL3 |
+---------------+---------------+
| ``local4`` | LOG_LOCAL4 |
+---------------+---------------+
| ``local5`` | LOG_LOCAL5 |
+---------------+---------------+
| ``local6`` | LOG_LOCAL6 |
+---------------+---------------+
| ``local7`` | LOG_LOCAL7 |
+---------------+---------------+
.. method:: mapPriority(levelname)
Maps a logging level name to a syslog priority name.
You may need to override this if you are using custom levels, or
if the default algorithm is not suitable for your needs. The
default algorithm maps ``DEBUG``, ``INFO``, ``WARNING``, ``ERROR`` and
``CRITICAL`` to the equivalent syslog names, and all other level
names to 'warning'.
.. _nt-eventlog-handler:
NTEventLogHandler
^^^^^^^^^^^^^^^^^
The :class:`NTEventLogHandler` class, located in the :mod:`logging.handlers`
module, supports sending logging messages to a local Windows NT, Windows 2000 or
Windows XP event log. Before you can use it, you need Mark Hammond's Win32
extensions for Python installed.
.. class:: NTEventLogHandler(appname, dllname=None, logtype='Application')
Returns a new instance of the :class:`NTEventLogHandler` class. The *appname* is
used to define the application name as it appears in the event log. An
appropriate registry entry is created using this name. The *dllname* should give
the fully qualified pathname of a .dll or .exe which contains message
definitions to hold in the log (if not specified, ``'win32service.pyd'`` is used
- this is installed with the Win32 extensions and contains some basic
placeholder message definitions. Note that use of these placeholders will make
your event logs big, as the entire message source is held in the log. If you
want slimmer logs, you have to pass in the name of your own .dll or .exe which
contains the message definitions you want to use in the event log). The
*logtype* is one of ``'Application'``, ``'System'`` or ``'Security'``, and
defaults to ``'Application'``.
.. method:: close()
At this point, you can remove the application name from the registry as a
source of event log entries. However, if you do this, you will not be able
to see the events as you intended in the Event Log Viewer - it needs to be
able to access the registry to get the .dll name. The current version does
not do this.
.. method:: emit(record)
Determines the message ID, event category and event type, and then logs
the message in the NT event log.
.. method:: getEventCategory(record)
Returns the event category for the record. Override this if you want to
specify your own categories. This version returns 0.
.. method:: getEventType(record)
Returns the event type for the record. Override this if you want to
specify your own types. This version does a mapping using the handler's
typemap attribute, which is set up in :meth:`__init__` to a dictionary
which contains mappings for :const:`DEBUG`, :const:`INFO`,
:const:`WARNING`, :const:`ERROR` and :const:`CRITICAL`. If you are using
your own levels, you will either need to override this method or place a
suitable dictionary in the handler's *typemap* attribute.
.. method:: getMessageID(record)
Returns the message ID for the record. If you are using your own messages,
you could do this by having the *msg* passed to the logger being an ID
rather than a format string. Then, in here, you could use a dictionary
lookup to get the message ID. This version returns 1, which is the base
message ID in :file:`win32service.pyd`.
.. _smtp-handler:
SMTPHandler
^^^^^^^^^^^
The :class:`SMTPHandler` class, located in the :mod:`logging.handlers` module,
supports sending logging messages to an email address via SMTP.
.. class:: SMTPHandler(mailhost, fromaddr, toaddrs, subject, credentials=None, secure=None)
Returns a new instance of the :class:`SMTPHandler` class. The instance is
initialized with the from and to addresses and subject line of the email.
The *toaddrs* should be a list of strings. To specify a non-standard SMTP
port, use the (host, port) tuple format for the *mailhost* argument. If you
use a string, the standard SMTP port is used. If your SMTP server requires
authentication, you can specify a (username, password) tuple for the
*credentials* argument. If *secure* is True, then the handler will attempt
to use TLS for the email transmission.
.. versionchanged:: 2.6
*credentials* was added.
.. versionchanged:: 2.7
*secure* was added.
.. method:: emit(record)
Formats the record and sends it to the specified addressees.
.. method:: getSubject(record)
If you want to specify a subject line which is record-dependent, override
this method.
.. _memory-handler:
MemoryHandler
^^^^^^^^^^^^^
The :class:`MemoryHandler` class, located in the :mod:`logging.handlers` module,
supports buffering of logging records in memory, periodically flushing them to a
:dfn:`target` handler. Flushing occurs whenever the buffer is full, or when an
event of a certain severity or greater is seen.
:class:`MemoryHandler` is a subclass of the more general
:class:`BufferingHandler`, which is an abstract class. This buffers logging
records in memory. Whenever each record is added to the buffer, a check is made
by calling :meth:`shouldFlush` to see if the buffer should be flushed. If it
should, then :meth:`flush` is expected to do the needful.
.. class:: BufferingHandler(capacity)
Initializes the handler with a buffer of the specified capacity.
.. method:: emit(record)
Appends the record to the buffer. If :meth:`shouldFlush` returns true,
calls :meth:`flush` to process the buffer.
.. method:: flush()
You can override this to implement custom flushing behavior. This version
just zaps the buffer to empty.
.. method:: shouldFlush(record)
Returns true if the buffer is up to capacity. This method can be
overridden to implement custom flushing strategies.
.. class:: MemoryHandler(capacity, flushLevel=ERROR, target=None)
Returns a new instance of the :class:`MemoryHandler` class. The instance is
initialized with a buffer size of *capacity*. If *flushLevel* is not specified,
:const:`ERROR` is used. If no *target* is specified, the target will need to be
set using :meth:`setTarget` before this handler does anything useful.
.. method:: close()
Calls :meth:`flush`, sets the target to :const:`None` and clears the
buffer.
.. method:: flush()
For a :class:`MemoryHandler`, flushing means just sending the buffered
records to the target, if there is one. The buffer is also cleared when
this happens. Override if you want different behavior.
.. method:: setTarget(target)
.. versionchanged:: 2.6
*credentials* was added.
Sets the target handler for this handler.
.. method:: shouldFlush(record)
Checks for buffer full or a record at the *flushLevel* or higher.
.. _http-handler:
HTTPHandler
^^^^^^^^^^^
The :class:`HTTPHandler` class, located in the :mod:`logging.handlers` module,
supports sending logging messages to a Web server, using either ``GET`` or
``POST`` semantics.
.. class:: HTTPHandler(host, url, method='GET')
Returns a new instance of the :class:`HTTPHandler` class. The *host* can be
of the form ``host:port``, should you need to use a specific port number.
If no *method* is specified, ``GET`` is used.
.. method:: emit(record)
Sends the record to the Web server as a percent-encoded dictionary.
.. seealso::
Module :mod:`logging`
API reference for the logging module.
Module :mod:`logging.config`
Configuration API for the logging module.
Doc/library/logging.rst
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